ISO 14001 is a standard that specifies the requirements for an effective Environmental Management System (EMS). It provides organizations with a structured framework to adopt sustainable practices, helping them manage their environmental impact, reduce risks, and comply with legal requirements. This certification also ensures that organizations are committed to continuously improving their environmental performance.

As a pioneer in the tech industry, Confiz recognizes the intricate link between innovation and sustainability. With global climate change and environmental degradation becoming increasingly urgent issues, we are committed to actively contributing to global sustainability efforts. By reducing our carbon footprint and implementing sustainable practices, we aim to lead by example, integrating responsibility into every facet of our business to foster a greener, more sustainable future. Hence, this certification is a major milestone in our journey to reinforce our commitment to environmental stewardship and drive positive change.

“As a responsible tech leader, we’re committed to innovating with sustainability at the forefront,” says Ahsan Saleem, General Manager Global SME. “This certification is a testament to our team’s dedication to creating a better future for all.”

Achieving this prestigious certification wouldn’t have been possible without the exceptional leadership of Mahnoor Imtiaz, Senior Process Audit Specialist. Certified in ISO 14001:2015 through Confiz’s sponsorship—a reflection of our commitment to investing in our people—Mahnoor single-handedly led the company’s internal EMS team, guiding them through the rigorous audit process from start to finish. Her precision, determination, and expertise were instrumental in achieving this milestone.

“Confiz is now part of an elite group of organizations prioritizing the planet’s well-being,” adds Mahnoor Imtiaz. “This achievement inspires us to innovate with sustainability at the forefront, fostering a better future for all.”

The certification journey kicked off with in-depth training sessions led by Mahnoor Imtiaz, equipping team members across various departments with essential auditing expertise and practical knowledge. Our dedicated EMS team included:

• People & Culture: Tayyaba Nisar, Umer Majeed

• Procurement: Muzzamil Ashraf

• Workplace & Community: Komal Sarwar

• IT Services: M Aamir Khan

• Legal & Compliance: Ahmed Abdullah

Following the training, Confiz’s internal team conducted a thorough internal audit, focusing on continuous improvement and identifying opportunities to enhance our processes. These insights laid the groundwork for a management review meeting, where actionable enhancements were solidified, perfectly priming us for the final step: the external audit.

The external audit was conducted by RICI Pakistan, one of the leading global providers of Third-Party Inspection, Testing, Calibration, and Certification services. Known for their adherence to international standards, RICI ensured Confiz met all EMS requirements with excellence and secured the ISO 14001 certification in record time!

This certification adds to our growing list of accomplishments, as Confiz is also certified in QMS (Quality Management Standard), ISMS (Information Security Management Standard), and ITMS (IT Service Management Standard). These certifications highlight our steadfast dedication to creating a culture where responsibility meets ambition and innovation leads the way.

For us, achieving ISO 14001:2015 reflects who we are. At Confiz, we believe in leading with purpose, fostering a sustainable future, and ensuring our operations contribute to a greener world. We’re excited to use this momentum to make an even bigger impact, blending environmental responsibility with our strategic growth initiatives and making an even greater difference in the years to come.

With 2.1 million users actively engaging with Copilot every month, organizations worldwide are benefiting from AI-driven experiences and streamlined processes. Microsoft Copilot Studio is a game-changer, enabling both technical and non-technical users to create generative AI-powered agents, fostering the transition to becoming truly AI-first organizations.

The latest update to Microsoft Copilot introduces autonomous agents, a significant leap in AI capabilities. These agents operate independently, reducing the need for constant prompts and driving greater efficiency.

In this blog, we will explore what autonomous agents are, how they differ from Copilot’s traditional functionality, and the transformative potential they hold for your organization.

What are Autonomous Agents in Microsoft Copilot Studio?

Autonomous agents in Microsoft Copilot Studio are essentially advanced AI-driven helpers designed to operate with minimal human intervention. You may call them the next-generation, AI-powered tools designed to execute tasks with minimal human oversight. These agents are the cornerstone of an AI-first business environment, enabling automation and efficiency across various functions.

If you’re wondering how Microsoft Copilot differs from autonomous agents, think of Copilot as your intelligent assistant, designed to streamline workflows and boost productivity by offering AI-driven insights and support. Copilot Studio takes this concept further by allowing users to create, manage, and customize autonomous agents tailored to specific organizational needs. Autonomous agents, on the other hand, function like modern AI-driven apps, capable of handling tasks independently—from simple prompt-response interactions to complex, fully autonomous operations.

Get familiar: What’s Copiloit studio and how is it empowering businesses?

How do Autonomous Agents work?

Agents automate and orchestrate business processes, assisting individuals, teams, or departments. Whether accelerating lead generation, processing sales orders, or optimizing supply chains, these agents work seamlessly through Copilot, reducing manual effort and driving operational excellence.

Designed to act autonomously, agents act autonomously by responding to signals within your business ecosystem and initiating tasks without requiring manual intervention. They can be configured to react to specific events or triggers originating from various tools, systems, or databases. Additionally, agents can be scheduled to execute tasks at regular intervals, such as hourly, daily, weekly, or monthly, ensuring consistent and timely operations.

Trust, reliability, and accuracy are fundamental to enabling agent autonomy within organizations. The true potential of these agents lies in their capacity to observe and track activities in real-world scenarios, driving better business outcomes by automating processes and making data-driven decisions with minimal human oversight.

Copilot Studio agents are powered by the latest AI models, including OpenAI’s O1 series. These advanced models are specifically designed for complex reasoning tasks, significantly enhancing the agents’ ability to tackle intricate problems and deliver more sophisticated solutions.

Autonomous Agents for Microsoft Dynamics 365: Unlocking AI-driven business capabilities

Autonomous agents are now a part of Microsoft Dynamics 365 too empowering organizations with AI-first business processes, enhancing sales, service, finance, and supply chain teams. By leveraging autonomous agents, businesses can scale operations, streamline workflows, and significantly improve customer experiences across different functions.

Let’s see how they are transforming these functions:

Sales: Accelerating lead generation and deal closure

Autonomous agents help sales teams focus on high-value customer relationships. For example, the Sales Qualification Agent in Microsoft Dynamics 365 Sales helps prioritize inbound leads, automating the process of researching and drafting personalized sales emails to initiate conversations. This automation allows sellers to concentrate on closing deals faster and more efficiently.

Operations: Optimizing processes for growth

In dynamic business environments, efficient operations are crucial. Autonomous agents assist in key areas like finance, procurement, and supply chain management, reducing manual work and enabling faster decision-making. For instance, the Supplier Communications Agent in Microsoft Dynamics 365 Supply Chain Management autonomously manages communications with suppliers, confirming order deliveries and addressing potential delays, thus optimizing procurement workflows.

Additional agents, such as the Financial Reconciliation Agent and Account Reconciliation Agent, simplify time-consuming tasks like data cleansing and matching transactions, speeding up the financial close process and enhancing cash flow visibility. The Time and Expense Agent ensures timely invoicing and project budget tracking, preventing revenue leakage.

Service: Revolutionizing customer experience

Autonomous agents also transform customer service operations. Contact centers can now automate routine tasks like managing knowledge bases and analyzing customer interactions to derive insights for continuous service improvement. The Customer Intent Agent, for example, learns from past conversations to enhance self-service capabilities, while the Customer Knowledge Management Agent keeps knowledge articles up-to-date, ensuring timely and relevant information is available to agents and customers alike.

Other service agents, like the Case Management Agent for Microsoft Dynamics Customer Service and the Scheduling Operations Agent for Microsoft Dynamics 365 Field Service, streamline case handling and technician scheduling, enabling more efficient service delivery and improving customer satisfaction.

Become an AI-first company with Confiz

Autonomous agents are key to reshaping operations across all business functions, driving cost savings, improving issue resolution, and enhancing service delivery. With the ability to adapt and learn, these agents create a seamless, AI-powered experience for both employees and customers. By integrating these capabilities into Microsoft Dynamics 365, businesses can embrace AI-first processes and accelerate their digital transformation journey.

At Confiz, we specialize in helping organizations transition to an AI-first approach. Our expertise in implementing Microsoft Dynamics 365 and integrating AI technologies ensures that your business can fully leverage these advancements. We are committed to helping you harness the power of AI to streamline operations, boost productivity, and drive success.

To learn more about leveraging AI in Dynamics 365, contact us at marketing@confiz.com.

For managed service providers, delivering proactive support is no longer enough. Building and growing a thriving business with satisfied customers demands a comprehensive strategy. Operational excellence becomes the cornerstone, achievable only through a structured, repeatable framework. This is where an Application Managed Services framework, designed around proven standards and strategies, becomes invaluable.

At Confiz, we specialize in providing managed services across key tech domains, including Microsoft Business Applications like Dynamics 365, Data and AI, and Cloud adoption and management. Our AMS framework is built on six core pillars: People, SOPs, Tools, KPIs, Insights, and Strategic Preemption. Together, these pillars create a robust ecosystem that ensures consistency, fosters innovation, and delivers measurable results.

In this blog, we will explore each of these pillars, providing actionable insights to help you build a best-in-class AMS framework. Whether you are a growing MSP or looking to refine your processes, these strategies will equip you to meet your customers’ needs and achieve sustainable success.

Strategic insights: Rethinking the traditional approach to managed services

6 pillars of an effective Application Managed Services Framework for service excellence

To establish a managed services framework that drives service excellence, it’s essential to implement a well-defined process tailored to your MSP business. This approach not only enhances customer satisfaction but also improves profitability. Without an effective framework, achieving scalable and consistent results becomes a challenge.

Drawing from our extensive industry experience, we have identified six core pillars that form the foundation of a service excellence ecosystem. These pillars enable consistent and continuously improving service quality for customers. Below is a visual representation of the AMS framework, illustrating the ecosystem that delivers these outcomes.

Let’s explore each of these pillars in detail to understand their role in delivering exceptional services:

1. People: The heart of service excellence

At the core of any successful AMS framework are the people delivering the service. Their skills, motivation, and engagement determine the quality of support your organization provides. However, retaining talent in a business like AMS can be challenging without a well-thought-out strategy.

Confiz’s People pillar focuses on fostering a high-performing, satisfied team by:

• Skill development: Conducting continuous skills gap assessments and offering tailored training programs to address weaknesses.

• Gamification: Making performance management engaging through leaderboards and rewards for top performers.

• Alignment with business goals: Ensuring personal KPIs are tied to the customer’s objectives, creating a sense of purpose.

• Reward & recognition: Celebrating achievements through public recognition and tangible incentives.

• Career growth opportunities: Providing cross-training, upskilling, and pathways to progress from L1 to L3 roles, encouraging team members to expand their expertise.

• Work satisfaction: Automating repetitive tasks to ensure intellectual stimulation and reduced burnout.

By implementing these strategies, we have achieved an impressive 85% retention rate and an eNPS score of 45, showcasing high levels of team engagement and satisfaction.

Read more: Debunk common myths about application managed services

2. SOPs: Standardizing operational excellence

Standard Operating Procedures (SOPs) ensure consistency, efficiency, and high-quality service delivery across all team members and shifts. They provide a reliable framework for daily operations, minimizing variability and enabling new hires to quickly adapt.

Key SOPs in the Confiz AMS framework include:

• Onboarding and offboarding: Streamlined processes to integrate or transition team members seamlessly.

• Duty rosters: Ensuring proper coverage with clear shift scheduling.

• Ticket lifecycle management: Defining every stage of a ticket’s journey, from creation to resolution.

• Escalation protocols: Clear steps for managing exceptions and escalating critical issues.

• Performance audits & feedback: Regular evaluations to identify areas of improvement and reward high performance.

• Customer reporting: Multi-level, multi-cadence reports to keep stakeholders informed about performance and system health.

By leveraging proven SOPs, we eliminate service inconsistencies and ensure operational excellence, regardless of team size or complexity.

2. Tools: Enabling productivity and collaboration

The right tools are essential for efficient AMS operations. From managing service requests to facilitating collaboration, tools act as enablers that simplify workflows and enhance productivity.

Confiz equips teams with industry-leading tools, including:

• Ticket management: Tools like ServiceNow, Jira, and Azure DevOps streamline issue tracking and resolution.

• Knowledge management: Platforms like Confluence, SharePoint, and ServiceNow Knowledge Base ensure quick access to critical information.

• Collaboration: Communication platforms like Microsoft Teams and Slack foster seamless team collaboration.

In addition to tool recommendations, we also use pre-configured templates, tool-specific SOPs, and other IT support best practices to help teams use these tools effectively.

4: KPIs: Driving accountability and performance

Key performance metrics are the benchmarks for measuring success in Application Management Services. Confiz’s framework focuses on creating balanced KPIs that address short-term results while safeguarding long-term ecosystem health.

KPIs are generally categorized into three levels:

• Individual KPIs: Assess the effectiveness of individual contributors (e.g., SLA compliance, ticket resolution rates).

• Team KPIs: Encourage collaboration and shared responsibility within shifts and teams.

• Business-aligned KPIs: Align with customer objectives, such as reducing sales order turnaround times or increasing revenue.

These metrics not only drive accountability but also create a culture of continuous improvement.

5: Insights: Data-driven decision making

Actionable insights are critical for optimizing AMS operations. Confiz’s AMS framework leverages real-time dashboards and predictive analytics to deliver insights tailored to different stakeholders.

Key capabilities include:

• Performance dashboards: Visualizing real-time team productivity and system health.

• Predictive analytics: Identifying potential issues before they escalate.

• Introspection analytics: Highlighting gaps in team or system performance for continuous improvement.

These insights empower you to make informed decisions for enhancing service delivery and reducing costs.

6: Strategic Preemption: Proactively preventing issues

The ultimate goal of Application managed services is to minimize disruptions by addressing potential issues before they arise. Strategic preemption focuses on reducing ticket volumes over time, ensuring a smooth and efficient support ecosystem.

Key strategies include:

• Root cause analysis: Identifying and resolving recurring issues to prevent future occurrences.

• Automation: Streamlining repetitive tasks to reduce manual intervention.

• Continuous improvement: Regularly updating processes based on insights and feedback.

This proactive approach not only improves system stability but also enhances user satisfaction and operational efficiency.

Partner with Confiz for Managed Services excellence

Achieving service excellence in managed services demands a holistic framework that brings together people, processes, tools, and proactive strategies. The best managed service providers rely on such proven frameworks to consistently deliver exceptional results.

At Confiz, our managed services framework is built on six foundational pillars designed to ensure consistent performance, boost operational efficiency, and align seamlessly with your business objectives.

Ready to enhance your managed services? Contact us at marketing@confiz.com to discover how our tailored AMS solutions can help drive your organization toward sustained success and service excellence.

To break free from these limitations, organizations are increasingly turning to data migration as a strategic move. Migrating data to more flexible, cloud-based, or hybrid environments has become a priority for forward-thinking businesses seeking to leverage their data effectively. Data migration helps businesses resolve the limitations of outdated systems but also unlocks opportunities for enhanced scalability, improved performance, and advanced analytics capabilities.

Data migration not only addresses the constraints of outdated systems but also opens doors to enhanced scalability, improved performance, and advanced analytics capabilities.

In this blog, we will explore what data migration is and the different types of data migration, helping your forward-thinking business make the best choice for managing and migrating your data.

What is data migration?

Data migration is the process of moving data from one storage system or computing environment to another to improve scalability, enhance performance, and support varying business needs. This migration means transferring data from legacy systems to modern data platforms, moving between storage formats, applications, or even cloud and hybrid environments. However, to achieve a successful and effortless data migration, organizations need a well-thought-out data migration strategy.

As enterprise organizations generate data at unprecedented rates, choosing the right environment to store and manage data has become an important priority. Moving to more flexible and efficient systems enables businesses to gain deeper insights, drive innovation, and maximize the value of their data.

The role of a data migration strategy

To ensure a successful and seamless data migration, organizations must develop a well-thought-out strategy to migrate to a cloud-based data platform. A data migration strategy serves as a roadmap, guiding businesses through the complexities of the process. It helps assess data quality, select appropriate data migration tools, and outline clear goals. Additionally, it identifies potential risks and ensures that data is transferred smoothly and securely, keeping disruptions to a minimum.

With a solid data migration plan in place, companies can confidently choose the best environment for their data, ensuring long-term success and optimizing the benefits of their migration efforts. A well-structured strategy supports the transition to high-capacity, optimized storage and empowers organizations to make the most of their data.

When should your business consider data migration?

Knowing when to consider data migration is key to keeping your business agile and efficient. Certain situations call for a thoughtful approach to moving and reorganizing data, ensuring it serves your organization’s evolving needs. Understanding these moments can help you make strategic decisions that drive growth and innovation. Let’s explore some key scenarios to understand when data migration makes the most sense for your business.

• Bringing together multiple data systems into one to simplify data management

• Moving to a cloud or hybrid environment for enhanced scalability

• Expanding and scale storage capacity

• Enabling the use of advanced tools and applications that require newer data systems

• Improving the ability to access, analyze, and gain insights from data

• Meeting new compliance requirements

• Achieving older, less frequently accessed data from legacy systems

• Repurposing data to serve new functions

• Transferring data ownership

Understanding types of data migration: Which approach fits your needs?

Planning a data migration process requires more than just technical know-how; understanding the types of migration options available can make all the difference in achieving a smooth, successful transition. Whether it’s upgrading storage, enhancing databases, modernizing applications, or moving to the cloud, each migration type serves a unique purpose. By choosing the right approach, businesses can keep data secure, improve accessibility, and set themselves up for sustainable growth.

Let’s take a closer look at the various types of data migration that can help your business transform data management and support its organizational goals.

1: Storage migration

Storage migration involves moving data from one storage device or system to another. This is often done to upgrade from legacy systems or on-premises storage to more modern solutions that offer better performance, increased capacity, or cost efficiency. Leveraging storage migration services doesn’t alter the underlying data formats, but it empowers companies to unlock faster performance, streamline data backups, and enhance data validation, leading to greater efficiency and reliability.

2: Cloud migration

Migrating data to the cloud is one of the most common data migrations types and involves transferring data or applications to a cloud environment (public, private, or hybrid cloud), to access the benefits of cloud computing, such as scalability, cost-effectiveness, and accessibility.

When considering data migration to the cloud, you have two main options:

• Online migration in which data is transferred over the Internet or a private WAN connection, ensuring a seamless, real-time move.

• Offline migration in which data is loaded onto a storage appliance and physically shipped from the source data center to the target cloud, offering a secure and efficient way to handle large volumes.

Explore more: Cloud migration simplified: Your guide to the Microsoft Cloud Adoption Framework for Azure.

3: Data center migration

Data center migration involves moving an entire data center environment to another, either physically relocating hardware or migrating workloads between data centers. This type of migration is typically motivated by cost-saving measures, the need for better infrastructure, or the consolidation of data centers.

Prior to a successful migration, ensure the following data center migration checklist:

• Create a detailed data center migration plan.

• Make sure all data is backed up and recovery processes are thoroughly tested before migration to prevent any data loss.

• Migration seamlessly integrates with existing applications and solutions.

• Identify your business case for migrating your existing data center to a new one.

• Conduct a thorough data center migration risk assessment to identify challenges and create contingency plans to tackle them proactively.

4: Database migration

Database migration, also known as database schema migration, involves transferring data from one or more source databases to target databases with the help of a database migration service. Once the migration is complete, all data from the original databases is fully moved into the new databases. At this point, users who previously accessed the old databases are directed to the new ones and the original databases are then shut down. For a simple understanding of database migration, refer to the following diagram.

5. Application migration

Application migration is the process of moving an application, along with its associated data, from one environment to another, such as from on-premises infrastructure to the cloud or between cloud providers. This type of migration is particularly challenging because applications are interconnected with other programs. Issues often emerge due to the unique data formats and models used by the source and target systems. Application cloud migration involves modifying the application to work in the new environment and ensuring that all application components, including databases, integrations, and workflows, function correctly in the new environment.

When migrating applications, do consider the following characteristics to understand your application’s value:

• Business impact

• Capability to meet key business needs

• Relevance and timeliness of data

• Scale, complexity, and ease of management

• Maintenance and development costs

• Enhanced value from cloud migration

Data migration risks: What should your business watch out for?

With more businesses moving their key applications beyond traditional cloud setups, the path to data migration brings both opportunities and hurdles. Choosing the right data migration solutions and leveraging reliable data services is only one side of the equation, there are real risks involved that significantly impact everything from data security to system compatibility.

Data loss or corruption

Data migration can be risky sometimes, with data loss or corruption being one of the biggest pitfalls. When transferring massive volumes, data might slip through the cracks, get altered, or even corrupted. Such mishaps disrupt operations, create compliance issues, and lead to costly inaccuracies, turning a beneficial migration into a potential business setback.

Downtime and disruptions

The data migration process isn’t always seamless. Some migrations require systems to go offline, risking interruptions that can ripple across the entire business. Poorly managed downtime can stall productivity, disrupt customer service, and throw a wrench in daily operations. Without careful planning, the promise of progress can quickly turn into an unwanted pause.

Performance and compatibility issues

Migrating data from legacy systems to modern data platforms often clashes in different data formats and structures, leading to compatibility issues that disrupt how data functions post-migration. If the process isn’t optimized, new systems struggle with data loads, slowing down performance and impacting productivity, and turning a promising upgrade into a performance bottleneck.

Inadequate testing

Skipping through data migration testing, hidden errors often surface only after going live, causing disruptions, data quality issues, and frustrating rework. Without proper testing, the migration’s smooth start can quickly become a cascade of problems.

How to get started with the data migration process?

Getting started with data migration can feel overwhelming, but breaking it down into manageable steps can simplify the migration process. Let’s walk you through a quick roadmap to guide you through a successful migration.

1. Assess current infrastructure

Evaluate your existing systems and data to understand what needs to be moved and identify any potential challenges.

2. Define migration goals and needs

Clearly outline what you hope to achieve with the migration, such as improved performance, scalability, or compliance.

3. Plan the migration process

Develop a detailed data migration plan that includes timelines, data mapping, and risk mitigation strategies to ensure a smooth transition.

4. Choose the right tools or partners

Select the technology or service providers that best align with your migration needs to facilitate an efficient and secure move.

Start a journey to effortless data migration with Confiz

When it comes to expert data migration services, Confiz truly stands out as a trusted partner. Our experienced team excels in managing even the most complex data migrations, whether you’re looking to transition databases, move to high-performance cloud environments, or optimize your existing storage solutions. We understand that every business has unique requirements, which is why we take a tailored approach to each project.

From developing a comprehensive migration strategy to executing a seamless transition, we prioritize minimizing disruptions to your operations while maintaining the highest standards of data integrity and security. Our goal is to make your data migration process as efficient and risk-free as possible, ensuring that your organization is fully equipped to leverage its data in new, innovative ways. Ready to make your data migration a success? Contact us at marketing@confiz.com, and let’s get started.

The Pakistan User Group Summit 2024 is a highly anticipated event bringing together professionals, enthusiasts, and organizations from the tech industry to explore advancements in Microsoft Power Platform and related technologies. The summit promises a mix of engaging sessions, a hackathon, networking opportunities, and insights from industry leaders. The event focuses on fostering collaboration and knowledge-sharing within the Microsoft tech ecosystem, covering tools like Power Apps, Power Automate, and Power BI.

Representing Confiz at the summit were Ahsan Fayyaz (VP Professional Services), Muneeb Ul Haq (Director Professional Services), Umar Naeem (Principal Software Engineer), and Muhammad Asad (Senior Director Professional Services). Our leadership team was excited to connect with professionals in the Microsoft Products & Platforms, share insights, and explore opportunities for collaboration and innovation.

As a proud bronze sponsor, Confiz was honored to contribute to the success of this event. Our team gave an insightful introductory session about Confiz, followed by an engaging session titled “Empowering Business with the Power of Microsoft Copilot,” presented by Muhammad Asad and Muneeb Ul Haq Gillani. Our goal was to showcase how technology can drive business success and how Confiz is leading the way in empowering organizations through Microsoft’s cutting-edge solutions.

The event also provided an opportunity for the attendees to connect with top-tier industry professionals, both local and international, who are experts in Microsoft Dynamics 365 and Power Platform. It was a great chance for everyone to learn from and network with leaders shaping the future of technology and accelerating their professional growth.

Pakistan User Group Summit 2024 promises to add immense value to Pakistan’s tech industry, fueling a growth-centric, skilled workforce. Confiz was proud to sponsor this event, driving impactful conversations and opening doors to new opportunities for Pakistan’s tech future. As we look ahead, Confiz remains committed to playing a pivotal role in empowering organizations with cutting-edge technology and building a thriving tech ecosystem in Pakistan and beyond.

Adding to the urgency, a recent study reveals that 56% of business executives are either unaware or unsure if their organizations even have ethical guidelines for using generative AI. This shocking statistic exposes a major gap in understanding and preparation, signaling a clear call to action for businesses to take generative AI ethics seriously in the age of data and AI.

In this blog, we’ll break down what AI ethics really mean, cover the five pillars of the ethics of generative AI, and share how your business can set up for success in this new era. Keep reading to get the full picture.

What is AI ethics? The moral compass for generative AI development

Ethics in AI refers to the guidelines and principles that govern the development and use of artificial intelligence in a way that is fair, transparent, accountable, and beneficial to society. As AI technology continues to evolve rapidly, the ethics of AI ensure that AI systems operate responsibly, avoiding harm and respecting fundamental human rights. These principles cover everything from the way data is collected and used to the potential societal impact of deploying AI technologies. Key areas of concern include privacy, fairness, accountability, and bias prevention.

AI governance plays a critical role in establishing frameworks and policies that uphold ethics in AI. Responsible AI governance ensures that AI systems are designed to be transparent so users understand how decisions are made and explainable so outcomes can be scrutinized and trusted. Additionally, it calls for a commitment to inclusivity, ensuring that AI technologies do not disproportionately disadvantage any particular group. In a nutshell, AI ethics and governance aim to balance technological advancement with societal well-being, creating solutions that enhance human life without causing unintended consequences.

Further reading: Gain trust and transparency with data governance in the age of generative AI.

Why is it important to consider ethics when using generative AI?

Ethics in AI has become a critical concern for organizations, as generative AI and similar technologies have far-reaching impacts on individuals, businesses, and society. International regulations like GDPR (General Data Protection Regulation), CCPA (California Consumer Privacy Act), UNESCO recommendations on the ethics of AI, OECD AI Principles, and WHO guidance on AI ethics play a crucial role in shaping the ethical landscape of generative AI. These laws emphasize the protection of personal data, transparency, and accountability, ensuring that AI systems respect privacy rights and prevent misuse. 

Ethical considerations of AI help ensure responsible use, foster trust, and minimize unintended harm. Here are the key reasons why ethics matter in generative AI:

1. Preventing harm: Generative AI can produce misinformation, biased content, or harmful outputs. Ethical guidelines mitigate these risks and protect users from negative consequences.
2. Ensuring fairness: AI systems can unintentionally perpetuate or amplify biases present in training data. Ethical practices promote fairness and inclusivity by addressing these biases.
3. Building trust: Transparent and ethical use of AI fosters trust among users, stakeholders, and the public, ensuring the technology is accepted and adopted responsibly.
4. Protecting privacy: Generative AI often processes vast amounts of data, raising privacy concerns. Ethical considerations ensure that data is handled securely and that it respects user consent.
5. Promoting accountability: Clear ethical standards help define accountability, ensuring developers and organizations take responsibility for AI’s outcomes and impacts.
6. Avoiding misuse: Generative AI can be misused for malicious purposes, such as creating deepfakes or spam. Ethical use helps prevent such exploitation.
7. Supporting long-term benefits: Ethical AI practices prioritize sustainable development and align with societal values, ensuring that advancements benefit humanity as a whole.

5 foundational pillars for building a responsible generative AI model

Recognizing the need for standards in the ethical use of generative AI is the first step toward responsible implementation. It’s essential to ensure this powerful technology drives positive change for businesses and society while minimizing unintended harm. The ethical considerations when using generative AI demand a proactive approach to identifying and addressing potential challenges before they evolve into real-world issues.

The second step is creating robust policies to guide ethical AI use. This involves understanding the foundational models behind generative AI and building frameworks that align with ethical principles. But what are the pillars of AI ethics that serve as the foundation for responsible practices?

At the heart of ethical AI are five key pillars:

Let’s explore how each of these principles forms the foundation for generative AI ethics, highlighting the responsibility of developers using generative AI.

Accuracy

Accuracy is paramount when it comes to building generative AI models. With the existing generative AI concerns around misinformation, engineers should prioritize accuracy and truthfulness when designing gen AI solutions. Developers must strive to create models that produce outputs that are not only relevant but also factual and contextually appropriate. This involves:

• Rigorous testing to measure how well the model performs against a set of known benchmarks.

• Data quality to train your model on high-quality, well-annotated data to minimize errors.

Authenticity

We live in an era where generative AI has blurred the lines between real and synthetic, creating a world where text, images, and videos can be convincingly faked. This new reality makes it more critical than ever to build generative AI models that can be trusted to deliver genuine, meaningful content. The generative AI model goals should be aligned with responsible content generation. Avoid enabling uses that can deceive or manipulate people, such as creating deepfakes or spreading misinformation.

Engineers have a responsibility to ensure that what their models create upholds the integrity and authenticity we rely on with various solutions, such as Deepfake detection algorithms, Retrieval Augmented Generation (RAG), or Digital watermarking, etc.

Privacy

Generative AI models have heightened concerns around data consent and copyrights, but one area where developers can make a real impact is by prioritizing user data privacy. Models trained on personal information come with significant risks: a single data breach or misuse can spark legal consequences and shatter user trust, a foundation that no successful AI system can afford to lose. Therefore, developers should consider:

• Data anonymization

Make user anonymity your default. Before training your models, ensure personal data is stripped of identifiable information. This way, you’re protecting user privacy while still leveraging valuable insights with data anonymization techniques.

• Data minimization

Follow principles like GDPR’s data minimization, which call for processing only what’s absolutely necessary. By collecting minimal data, you not only enhance privacy but also simplify compliance with data regulations.

Anti-bias

Generative models are only as fair as the data they learn from. If fed biased information, they will inadvertently perpetuate or even amplify societal biases, which can lead to public backlash, legal repercussions, and damage to a brand’s reputation. Unchecked bias can compromise fairness, trust, and even human rights. That’s why building bias-free AI requires periodic audits to ensure your generative AI model evolves responsibly.

To build responsible models, developers must use bias detection and mitigation techniques (adversarial training and diverse training data) both before and during training to actively identify and reduce inequalities in generative AI models.

Transparency

When it comes to building generative AI models, achieving transparency is the foundation of trust. Without it, users are left in the dark, unable to fact-check or evaluate AI-produced content effectively. To build trust and accountability, AI systems must be open and clear about how they operate.

To build trust, developers should consider taking a few measures to boost transparency in generative AI solutions, such as:

• Design models that can explain their decision-making processes in a way that users can easily understand. Use interpretable algorithms and provide clear documentation outlining how your model works, including its limitations and areas of uncertainty.

• Be upfront about when and how generative AI is used, especially in contexts where it could mislead, such as automated content generation or AI-driven recommendations.

More insights: How to start your generative AI journey: A roadmap to success.

Responsible use of generative AI: How to set up your business for ethical generative AI use

Although generative AI brings incredible opportunities for businesses, using it responsibly takes more than just ticking boxes. It’s about understanding the ethics of AI in business and making thoughtful choices that build trust with your customers, employees, and stakeholders, all while keeping potential risks in check. Let’s explore some key strategies to help your business use generative AI in a way that’s both ethical and impactful:

Get clear on your purpose

Before getting started right away with generative AI, start by pinpointing exactly how your business plans to use it. Will it help generate content, improve product development, or streamline customer service? Defining your use cases upfront not only sharpens your strategy but also ensures you can align your AI initiatives with ethical principles from the get-go.

Set the bar high with quality standards

Don’t leave the quality of your generative AI outputs to chance, set clear, high standards from the start. Think about what matters most: accuracy, inclusivity, fairness, or even how well the AI matches your brand’s tone and style. Regularly review and fine-tune your AI’s performance and be ready to step in and retrain it as needed. After all, ethical AI use means keeping a close eye on what your technology is producing and making continuous improvements.

Establish company-wide AI guidelines

Make sure everyone in your organization is on the same page when it comes to the responsible use of generative AI. Develop clear, comprehensive AI policies that apply across all teams and departments. Cover everything from ethical principles and data privacy to transparency, compliance, and strategies for minimizing bias. By creating a unified playbook, you’ll promote professional integrity and help ensure that your generative AI practices are ethical and consistent throughout the company.

Cultivate a culture of responsibility

Make ethics a team sport! Encourage open discussions about the risks and rewards of generative AI and involve your team in shaping ethical practices. Making ethics part of your culture empowers everyone to use AI thoughtfully and responsibly. When everyone feels empowered to contribute, your business becomes better equipped to use Generative AI responsibly and make smarter, more ethical decisions.

Keep your policies up to date

AI technology and regulations are constantly evolving, so don’t let your policies become outdated. Make it a habit to regularly review and refresh your generative AI guidelines, ensuring they stay in line with the latest ethical standards, legal requirements, and technological advancements. Staying proactive with updates helps your organization stay compliant and ethically sound as AI continues to transform the business landscape.

Empower your business with Confiz’s gen AI expertise

Generative AI is revolutionizing industries and setting new benchmarks for innovation, making the call for ethical and thoughtful implementation louder than ever. As this game-changing technology becomes mainstream, enterprises face a critical responsibility: using AI in ways that are both safe and responsible.

At Confiz, we understand the complexities of generative AI and the ethical challenges that come with it. With proven expertise in generative AI proof of concepts (POCs), we help businesses identify the right generative AI applications that drive growth and uphold ethical standards. Our approach ensures that your AI solutions are accurate, fair, and trustworthy, setting your business up for long-term success. Let’s talk about how Confiz can elevate your business with ethical generative AI solutions. Reach out to us at marketing@confiz.com today.

• How do we efficiently manage structured data for business intelligence and reporting?

• What’s the best way to process and analyze unstructured datasets for advanced use cases like machine learning?

• Can one platform handle all our data needs effectively?

This dilemma is further complicated by the need to balance performance, scalability, and cost-efficiency, all while ensuring that the data analytics infrastructure can keep up with ever-increasing demands. As companies strive to store, process, analyze, and extract valuable insights from their data, selecting the right data platform has never been more crucial. Azure Synapse Analytics and Databricks often emerge as leading contenders, offering powerful solutions to meet the complex demands of modern data analytics.

These platforms are not interchangeable. They excel in different areas and address distinct business challenges. This blog will help you understand the differences between Azure Synapse Analytics and Databricks, helping you decide which one’s worth adding to your tech stack.

What is Azure Synapse? A powerful cloud-based analytics service

Previously known as Azure SQL Data Warehouse, Azure Synapse Analytics is the official name of the service, and it is often simply referred to as Azure Synapse for short.

This comprehensive enterprise analytics service, offered by Microsoft, is designed to bring together big data analytics and data warehousing capabilities into a unified environment. It enables organizations to analyze, manage, and visualize data from multiple sources, whether structured, semi-structured, or unstructured.

Azure Synapse combines SQL technologies for enterprise data warehousing and Spark for big data processing. It also includes Data Explorer for analyzing logs and time series data, along with Pipelines for seamless data integration and ETL/ELT workflows. It also offers strong integration with other Azure services like Power BI, CosmosDB, and Azure Machine Learning, providing a comprehensive analytics solution.

As a key part of Microsoft’s Azure ecosystem, Azure Synapse Analytics empowers enterprises to seamlessly consolidate data integration, management, and analytics into one unified platform. By unifying data warehousing, big data analytics, and machine learning capabilities, it helps organizations break down data silos and optimize workflows. This integration enables faster, more efficient insights, empowering businesses to unlock deeper and actionable intelligence from their data.

Azure Synapse Analytics features: What makes it a must-have for businesses?

With an understanding of what is Azure Synapse Analytics and its role in transforming data management and analysis, let’s explore some of it’s key features that make it such a powerful tool.

• Unlimited analytics potential

Azure Synapse Analytics breaks down silos, enabling businesses to seamlessly analyze data across data warehouses, data lakes, operational databases, and big data analytics systems. This scalability ensures that regardless of data size or complexity, you can generate insights that drive informed decision-making. By offering integration with tools like Power BI and Azure Machine Learning, Synapse allows organizations to expand their analytics capabilities without compromise.

Quick read: Data Lake vs Data warehouse: 6 key differences you need to know.

• Accelerated development time and collaboration

One of the standout features of Azure Synapse is its ability to significantly reduce development time. Through its integrated machine learning models, you can apply advanced analytics directly to your intelligent applications without the need for data movement. Moreover, sharing data across teams is as simple as a few clicks, fostering collaboration and speeding up project timelines. This streamlined approach enhances efficiency while enabling teams to deliver results faster.

• Brings together everyone in one workspace

Microsoft Azure Synapse Analytics provides a unified workspace that brings together data engineers, database administrators, data scientists, and business analysts on a single platform. This integration eliminates the need for fragmented tools and fosters collaboration across departments. Whether it’s building pipelines, managing databases, or generating actionable insights, everyone can work seamlessly within the same environment, leading to more cohesive and effective analytics workflows.

• Streamlines data workflows for instant insights

Azure Synapse makes moving data between operational databases and business applications effortless, enabling near-real-time insights. This convergence of data workloads ensures that businesses can react to changes and opportunities as they arise, driving agility and responsiveness.

Whether you’re analyzing sales data or monitoring customer interactions, Synapse Analytics Azure enables you to stay ahead by delivering insights when they matter most.

• Keeps your data secure and compliant

As data becomes extremely important to modern businesses, securing and protecting privacy is non-negotiable. With features like automated threat detection and always-on encryption, your data remains protected from unauthorized access and potential breaches. This robust security framework ensures compliance with industry standards while giving businesses peace of mind for enterprise data management.

What is Databricks: The ultimate unified data analytics platform

Databricks is a dynamic, unified, open analytics platform that revolutionizes big data processing, engineering, data science, and machine learning. Databricks unified data analytics platform leverages Apache Spark, an open-source system renowned for its speed and simplicity in big data processing. This managed Apache Spark Databricks platform optimizes various workloads, including ETL (Extract, Transform, Load), streaming analytics, data warehousing, and machine learning.

Beyond its analytics power, Databricks excels with advanced features for unified data governance, top-tier security, and seamless data sharing. These capabilities make it a game-changer for modern, data-driven enterprises. Microsoft also offers Azure Databricks, an Azure integration service that combines the power of Azure with Databricks (a co-developed data and AI service for data engineering, data science, data analytics, and machine learning workloads). This robust data analytics platform offers a great solution to organizations to transform the overwhelming data deluge into actionable intelligence.

Azure Synapse vs Databricks: A comparative analysis

When it comes to Azure Synapse and Databricks, the choice isn’t about which is better but which is best for your unique business needs. While powerful in their own rights, Azure Synapse and Databricks cater to different use cases and excel in distinct areas.

Let’s walk you through the comparative analysis of Azure Synapse Analytics vs. Databricks, highlighting features to enhance your data journey.

Difference 1: Azure Synapse vs Databricks – Core purpose

Azure Synapse

Azure Synapse Analytics is a comprehensive platform primarily focused on data integration, warehousing, and large-scale analytics. It is tailored for analyzing structured and semi-structured data, making it ideal for businesses prioritizing traditional business intelligence and advanced analytics at scale.

Databricks

Databricks serves as a unified data analytics platform for big data analytics, data engineering, machine learning, and AI development. The platform is ideal for organizations analyzing large-scale datasets, managing real-time streaming, and developing advanced machine learning models efficiently.

Difference 2: Azure Synapse vs Databricks – Workload specialization

Azure Synapse

Azure Synapse Analytics is optimized for business intelligence (BI) and data warehousing use cases. It specializes in querying structured data using T-SQL and is ideal for batch-oriented reporting and analytics.

Databricks

Databricks is tailored for data engineering, data science, and AI workloads, offering exceptional support for unstructured, semi-structured, and structured data. It is particularly well-suited for iterative workflows, such as machine learning model development and advanced analytics.

Difference 3: Azure Synapse vs Databricks – Integration with Azure

Azure Synapse

Azure Synapse Analytics is a fully native Azure service with deep integration into the Azure ecosystem. It connects seamlessly with tools like Azure Data Factory and Power BI, offering a unified workspace that supports both SQL and Spark-based workflows. This makes Synapse an ideal choice for organizations heavily invested in the Azure platform.

Databricks

Databricks also integrates with Microsoft Azure. Azure Databricks architecture offers a scalable, secure, and integrated platform for processing and analyzing large volumes of data within the Azure cloud environment. It tightly integrates with multiple Azure services such as Azure Blob Storage, Azure Data Lake Storage, Azure SQL Database, and Azure Synapse Analytics. This integration allows for efficient data ingestion, storage, and processing within the Azure ecosystem.

Difference 4: Azure Synapse vs Databricks – Analytics and machine learning

Azure Synapse Analytics integrates with Power BI, providing a seamless solution for creating dynamic, interactive reports and insightful dashboards. With built-in SQL-based analytics tools, it’s user-friendly, enabling business analysts to uncover insights easily and without steep learning curves.

On the other hand, Databricks is a powerhouse for advanced data science and machine learning. With robust support for Python, R, and Scala, Databricks empowers data scientists and engineers with versatile tools for advanced analytics. Features like MLflow streamline end-to-end machine learning workflows, making it the go-to platform for driving innovation with cutting-edge AI.

Difference 5: Azure Synapse vs Databricks – Pricing model

Azure Synapse Analytics offers a flexible Pay-As-You-Go (PAYG) model, ensuring you pay only for what you use. The Azure Synapse cost is scalable, accommodating everything from small queries to large enterprise workloads. With transparent Azure Synapse Analytics pricing, businesses can optimize their analytics investments while leveraging versatile data solutions.

Databricks also uses a PAYG model, charging based on the number of Databricks Units (DBU) consumed. Discounts are available for committed usage, while costs vary with workload intensity, offering flexibility to optimize performance and budget.

Making the right choice: Azure Synapse or Databricks

When choosing between Azure Synapse Analytics and Databricks, there’s no one-size-fits-all solution. The right choice depends entirely on your business needs and priorities. To make the decision easier, we’ve outlined key scenarios for each platform:

• Go with Databricks if you focus on data engineering, AI, or processing massive datasets. Its flexibility and advanced analytics capabilities make it perfect for machine learning and cutting-edge data science workflows.

• Opt for Azure Synapse Analytics if your priority is business intelligence, data warehousing, or structured data analytics. Its seamless integration with Azure services like Power BI makes it ideal for organizations deeply embedded in the Azure ecosystem.

With these insights, you’re one step closer to finding the perfect fit for your analytics journey! You can also use the two platforms together, as Azure Synapse seamlessly integrates with Azure Databricks. This integration enables organizations to harness the unique strengths of both platforms for maximum efficiency.

Empower your business with smart data analytics today

Azure Synapse Analytics and Databricks bring powerful capabilities to the table, each excelling in different aspects of data management and analytics. Ultimately, choosing these two platforms depends on your specific business needs.

At Confiz, we understand the challenges of choosing the right platform and the complexity of managing and analyzing large datasets. Our data analytics services are designed to help businesses navigate these decisions and make the most of their large datasets. Our experts help you define and implement a tailored data analytics strategy streamlining data collection, management, analysis, and utilization. Contact our experts at marketing@confiz.com to explore how we can enhance your data analytics journey and drive insights.

And this is just the beginning. As generative AI becomes a core component of workplace operations, the opportunity extends beyond individual productivity. Copilot is setting a new standard by empowering employees to excel in writing, designing, coding, analyzing data, and more. It doesn’t just streamline tasks – it amplifies expertise, elevating work quality from good to exceptional.

According to Microsoft’s Work Trend Index Special Report, here are notable findings from early Copilot users:

There’s no doubt that Microsoft Copilot and generative AI are transforming the way we work, opening new possibilities across industries. Copilot has been seamlessly integrated into various Microsoft products, including Dynamics 365 applications, bringing AI-driven efficiency and innovation to businesses.

However, navigating the diverse AI capabilities across Microsoft products can be overwhelming. This guide simplifies the key features of Gen AI and Copilot in Dynamics 365, providing you with a clear starting point to unlock the potential of AI tools for business success.

Learn more: Discover Microsoft Dynamics 365 Copilot and its role in transforming business operations with AI insights.

Getting familiar with AI: Copilot in Dynamics 356

Microsoft Copilot enhances the Dynamics 365 ecosystem by delivering secure, privacy-compliant AI capabilities. It uses Azure OpenAI Service, built on Microsoft’s Responsible AI standards, ensuring that generative AI tools align with enterprise-level security and compliance expectations.

Here is a quick introduction on how Copilot works in Dynamics 365 and Power Platform:

How Copilot in Dynamics 365 is revolutionizing business efficiency and operations?

Copilot for Dynamics 365 is an AI-powered assistant designed to optimize productivity and streamline business processes across key departments like sales, customer support, supply chain management, finance, and marketing. With its chat-based interface, it provides instant insights such as summaries of sales opportunities, lead updates, meeting preparation, and account news.

Integrated with Outlook and Teams, Copilot enhances data management and utilizes generative AI to automate tasks such as record summarization and email creation, allowing teams to concentrate on high-value activities.

Discover more:

• Unlock the power of Copilot in Dynamics 365 Customer Engagement

• Enhance efficiency with Copilot in Dynamics 365 Finance and Operations

How do Dynamics 365 Applications use AI?

Dynamics 365 applications leverage the power of AI through Microsoft Azure services. Azure provides a secure and reliable foundation, adhering to Microsoft’s Responsible AI standards. This ensures enterprise-level security, privacy, and compliance, delivering AI solutions customers can trust.

How does Microsoft Azure support Generative AI?

Generative AI is a form of artificial intelligence that creates new content or data based on user input or prompts. Examples include generating text, creating images, composing music, or synthesizing speech.

Microsoft offers a variety of AI models and services through Azure, including Azure Cognitive Services, Azure Machine Learning, and the Azure OpenAI Service. The Azure OpenAI Service provides access to advanced models like GPT-4 and DALL-E, enabling businesses to perform tasks such as text generation, image creation, and conversational AI.

Dynamics 365 applications integrate Azure OpenAI Service to deliver generative AI capabilities that enhance productivity and streamline operations. These tools not only empower business users but also offer opportunities for Microsoft partners to integrate these capabilities into their own solutions.

How Generative AI is transforming businesses?

Generative AI is revolutionizing industries with its ability to create content, automate tasks, and enhance customer interactions. Here are some key benefits of generative AI in various aspects of businesses:

• Streamlined content creation and design: Generative AI enables businesses to quickly generate high-quality text, visuals, and media, saving time and resources for marketing and creative teams.

• Accelerated process automation: With AI-driven automation, repetitive tasks are handled seamlessly, improving efficiency and allowing teams to focus on strategic initiatives.

• Tailored marketing campaigns: Generative AI analyzes customer data to craft personalized marketing messages, increasing engagement and boosting conversion rates.

• Smart chatbots and virtual assistants: AI-powered bots deliver 24/7 customer support, answering queries and resolving issues in real time, enhancing customer satisfaction.

• Innovative product and service development: By analyzing market trends and generating ideas, generative AI helps companies create innovative solutions tailored to customer needs.

• Enhanced predictive analytics and forecasting: AI models process large datasets to provide accurate business forecasts, helping organizations make informed decisions and reduce risks.

Read more: Explore how generative AI is transforming the retail industry?

How to get access to AI in Dynamics 365?

To begin using AI in Dynamics 365, you need an Azure subscription and an Azure OpenAI Service account. Here’s a simple guide to help you take the first step:

• Get an Azure Subscription: Sign up for Azure and request access to Azure OpenAI Service. This can be done via the Azure portal.

• Choose models: Select from pre-trained AI models like GPT-4 or DALL-E based on your needs.

• Deploy and test: Set up the service in the Azure portal and experiment with different configurations. While you have the option to customize, train, and deploy models using your own data and parameters, this step is often unnecessary since Azure OpenAI models are pre-trained on extensive datasets, offering robust capabilities right out of the box.

Once completed, you can begin developing your Copilot experience to enhance workflows and productivity.

Tips and guidelines for giving effective prompts to Generative AI

A prompt serves as the input you provide to a model to generate an output, which can include text, images, or a combination of both. Crafting an effective prompt is key to obtaining high-quality, relevant results. Below are some pitfalls to avoid and best practices to follow when creating prompts:

• Be clear and specific: Clearly state what you want the model to do and the type of output you expect.

• Provide context: Include sufficient details about the task and domain to help the model understand your requirements.

• Use examples and keywords: Guide the model by incorporating examples, relevant keywords, and formatting to shape the output.

• Avoid ambiguity: Steer clear of vague or misleading prompts that may confuse the model or result in inaccurate outputs.

• Test and refine: Experiment with different prompts across scenarios to assess the model’s performance and reliability.

• Review outputs: Always verify the generated outputs for accuracy, quality, and ethical considerations before integrating them into workflows.

Summing up

AI in Dynamics 365 offers immense potential for businesses across industries. With features like Microsoft Copilot and generative AI models, you can optimize operations, improve customer engagement, and stay ahead in a competitive market. Ready to start your AI journey? Dive into Dynamics 365 with confidence and take your business to the next level!

To leverage the benefits of Copilot in Dynamics 365, reach out to us at marketing@confiz.com.

According to Forrester’s Total Economic Impact (TEI) study conducted in April 2024, Dynamics 365 ERP can yield a 106% ROI and generate a Net Present Value (NPV) of $8.09 million within the first three years of deployment. Now, with the addition of AI capabilities through Copilot, this business intelligence platform is set to elevate business operations even further.

Whether your goal is to deploy, optimize, or customize Dynamics 365 Finance and Operations (ERP) or Dynamics 365 Customer Engagement (CRM), partnering with a Microsoft Dynamics 365 consultant or implementation partner can be instrumental in achieving a successful digital transformation.

Finding the right Dynamics 365 partner can feel overwhelming, given the wide range of options available. In this blog, we will introduce you to the top Dynamics 365 partners in the USA and explore why choosing the right partner can make a significant difference in your business transformation journey.

How can a Dynamics 365 Partner help your business?

There is an extensive ecosystem of top Microsoft Dynamics 365 partners, each equipped to provide expert guidance and comprehensive support for every stage of your journey. From consulting and assessment to implementation and optimization, the right partner can ensure you make the most of your Dynamics 365 investment.

Here are three key ways a trusted Dynamics 365 implementation partner can benefit your business:

1. Choose the right solutions: A trusted partner will help you identify which Dynamics 365 applications best align with your current and evolving business needs, ensuring you invest in solutions that provide maximum value and scalability for your operations.
2. Customize and extend existing solutions: The right partner doesn’t just implement off-the-shelf solutions – they help you transform your business processes by tailoring Dynamics 365 to your unique requirements. Whether it’s integrating partner applications for advanced industry-specific features or customizing workflows to fit your operations, a skilled partner ensures your ERP or CRM systems are seamlessly aligned with your business goals.
3. Continuous support and guidance: Working with a Dynamics 365 partner goes beyond basic consulting and implementation. You gain access to ongoing support, expert insights, and proactive recommendations for optimization. This helps you stay at the forefront of industry trends and ensures your system continues to deliver value as your business evolves.

Best Microsoft Dynamics 365 partners in USA: Our top picks

As mentioned earlier, partnering with the right Microsoft Dynamics 365 implementation partner who can provide end-to-end support, from consultation to implementation and ongoing assistance, can make a significant difference in achieving success.

To help you find the best fit, we’ve curated a list of the top 5 Microsoft Dynamics 365 partners in the USA. These consultants were selected based on their expertise, customer satisfaction, and proven project success. Explore their offerings and choose the partner that aligns best with your business needs and goals.

1: Confiz

Confiz, headquartered in the USA, is a leading Microsoft Dynamics 365 implementation partner renowned for its deep expertise in streamlining business operations and accelerating digital transformation. With 18 years of experience and over 250 specialized Dynamics 365 consultants, Confiz is uniquely positioned to help businesses modernize their operations, automate critical processes, and gain actionable insights to drive growth and profitability. Serving a diverse range of industries, Confiz’s clientele includes Fortune 100 companies that trust the firm to deliver impactful, future-ready solutions.

Leveraging the full Microsoft tech stack – including Dynamics 365 Finance and Operations, Dynamics 365 Customer Engagement, Microsoft Power Platform, and AI-powered tools like Microsoft Copilot – Confiz empowers organizations to enhance customer engagement, optimize business processes, and achieve transformative results.

The company also excels in digital transformation consulting and custom application development tailored to meet specific business needs. In addition, Confiz has created a comprehensive suite of industry-specific IPs and accelerators designed to address unique challenges and drive business modernization, enabling businesses to maximize the value of their Microsoft Dynamics 365 investments.

Recognized for its client-focused approach, industry knowledge, and ability to deliver future-ready Dynamics 365 solutions, Confiz has a global presence with offices in the USA, UAE, KSA, Estonia, and Pakistan.

Core services offered by Confiz

• Dynamics 365 Solutions: Providing end-to-end services for Microsoft Dynamics 365, including consultation, implementation, upgrades, optimization, integrations, customizations, and ongoing support.

• Microsoft Power Platform Services: Empowering businesses to automate processes, build custom apps, and create insightful dashboards using tools like Power BI, Power Apps, Power Automate, and Power Virtual Agents.

• Application Managed Services: Ensuring optimal system performance with ongoing support.

• Data and AI: Driving actionable insights through advanced analytics and AI.

• Cloud Services: Migrating and managing cloud-based solutions for seamless operations.

• Software Development: Custom application development to meet specific business requirements.

• Industry-Specific Solutions: Specialized IPs and accelerators designed to optimize operations in industries such as retail, trading and distribution, supply chain, automotive, e-commerce, and more.

Confiz stands as a trusted partner for businesses seeking to harness the full potential of Microsoft Dynamics 365 and achieve transformative results.

2: Dynamics Square

Dynamics Square brings over 12 years of experience in helping businesses of all sizes implement Microsoft ERP and CRM solutions. As a trusted Microsoft Dynamics 365 Partner in the USA for ERP and CRM solutions, Dynamics Square specializes in deploying Microsoft Dynamics 365, Business Central, Microsoft Power BI, and other Microsoft products to support seamless operations. With a team of 150+ skilled Microsoft consultants, Dynamics Square offers comprehensive services, including implementation, support, and upgrades, backed by an impressive track record of end-to-end solution delivery.

With their services spread in USA, UK and Canada, Dynamics Square’s team excels in creating customized Dynamics-based solutions that enhance customer management across various domains such as sales, marketing, customer service, omnichannel experiences, and self-service. Their deep understanding of client needs and commitment to quality enables them to deliver effective and scalable digital solutions.

Their services range from:

• ERP consulting, implementation, and support

• Digital transformation

• Digital process automation

• Application development

• On-premises-to-cloud application migration

• Data analytics

• Software testing and quality assurance (QA)

3: Hitachi Solutions

Hitachi Solutions, recently recognized as the 2024 Microsoft Partner of the Year, is a leader in Dynamics 365 consulting with over 20 years of experience across ERP, CRM, and various industry-focused solutions. Their end-to-end services extend from initial implementation through to long-term support and optimization, with capabilities for integrating, customizing, and training on Dynamics 365 applications. Known for their industry-specific IP, Hitachi Solutions delivers tailored solutions that meet unique business needs, enhancing the core functionalities of Dynamics 365 and driving meaningful results for clients.

Hitachi Solutions’ services include:

• Dynamics 365 ERP & CRM Services

• Advisory services

• Managed Services

• Application & system modernization

• Data & AI services

• Cloud services

• Security and governance

4: Saglobal

sa.global is an AI-powered Microsoft Dynamics 365 consultant and partner that specializes in Dynamics 365 solutions for project-driven businesses. With over 30 years of experience and three global delivery centers, they help clients transform and modernize their operations by implementing industry-specific cloud solutions. Their approach is rooted in understanding the unique challenges of project-based companies and utilizing AI to streamline processes, increase productivity, and drive innovation.

Services offered by sa.global include:

• Consulting services

• Dynamics 365 services

• Implementation services

• Cloud migration and management services

• AI and Data Services

sa.global also offers industry-specific IP solutions that extend Dynamics 365’s capabilities, making it a preferred partner for project-based companies looking for specialized and scalable applications.

5: Encore Business Solutions

Encore Business Solutions is a distinguished Microsoft partner specializing in Dynamics 365 ERP, CRM, and cloud technologies. With over 30 years of experience, Encore has built a strong reputation in Canada and the U.S., helping organizations streamline operations through tailored Microsoft solutions. Their services include implementation, integration, support, and advisory, covering a range of Microsoft products like Dynamics 365, Power Platform, and Azure.

Encore Business Solutions’ services include:

• Microsoft Dynamics ERP & CRM solutions – Comprehensive ERP solutions for core business processes and CRM for managing relationships.

• Implementation & integration – Expert deployment and integration for seamless operations.

• Custom Development – Tailored applications to meet specific organizational needs.

• Training & support – Ongoing support and training to maximize solution use.

• Business intelligence & data analytics – Leveraging Power BI and other analytics tools for insights.

• Cloud services – Office 365 and Azure for secure, scalable cloud environments.

• Managed services – Full support for software lifecycle needs, ensuring continuity and performance over time.

Why choosing the right Dynamics 365 Partner matters?

Choosing the right partner for Dynamics 365 significantly affects your organization’s ability to achieve a successful digital transformation, enhance productivity, and maximize return on investment. Here’s why selecting the right partner makes a difference:

• Industry-specific expertise: A strong Dynamics 365 partner brings tailored knowledge and solutions, addressing challenges unique to your sector.

• Customized solutions: The right partner ensures that configurations align with your business processes, enabling seamless operations.

• Ongoing support & maintenance: Quality partners provide continuous support, ensuring systems are optimized and responsive to new needs.

• Proven implementation strategies: Experienced partners reduce risks with a structured approach, minimizing disruptions.

• Scalability: Reliable partners offer solutions that grow with your business, ensuring long-term value.

• Training & change management: They provide training resources, helping teams adapt and fully utilize new systems.

• Enhanced ROI: Expert partners focus on solutions that directly contribute to better resource allocation and operational efficiency, maximizing your return.

Learn more: Check out our complete guide to selecting the right Dynamics 365 implementation partner.

Summing up

In a landscape where selecting the right Dynamics 365 partner is crucial for business success, these top five U.S.-based partners for 2025 stand out for their proven expertise, industry focus, and commitment to customer satisfaction. Each offers unique strengths, helping organizations transform their operations and gain a competitive edge.

If you’re exploring your options, consider Confiz, a trusted Microsoft Dynamics 365 partner in the USA, known for delivering customized solutions aligned with your unique business objectives. With a proven record in consulting and rapid Dynamics 365 F&O and CRM implementations, Confiz is dedicated to helping companies scale efficiently and accelerate their digital transformation journey. Experience our expertise first hand by scheduling a personalized demo or contact us at  marketing@confiz.com for more information.

“The total size of the records in your joined Select statement is 224230 bytes, but Microsoft Dynamics 365 for Finance and Operations is by default performance-tuned not to exceed 196608 bytes.”

If you have encountered the record size limit error in Dynamics 365 Finance and Operations and are unsure how to proceed, this guide will walk you through understanding the issue and provide step-by-step solutions to resolve the joined record size limitation.

What does the joined record size limitation error mean?

This error message indicates that the system’s joined record size limit has been exceeded. In simple terms, the system restricts the maximum amount of data that can be joined and retrieved in one query. This limitation is designed as a performance safeguard, as handling large data sets can impact overall performance. However, there are scenarios where this default buffer limit can pose a barrier to accessing the necessary data.

Understanding the root cause of this form error?

The primary cause of this error lies in the global buffer size setting for forms within Dynamics 365 Finance and Operations. This buffer acts as a memory allocation that temporarily holds data when joining records. By default, the buffer space is capped at 196608 bytes (about 196.08 KB), which is generally sufficient for most standard operations. However, if your data volume exceeds this limit, the system will prevent form loading to avoid performance degradation.

In this case, the required buffer size for the selected data was 224230 bytes, exceeding the system’s default configuration. Therefore, an adjustment is necessary to increase the buffer size to match the needs of your data retrieval, allowing forms to load without issue.

Let’s explain this through screenshots:

The defined buffer size for default is 196608 bytes and its equal to 196.08 Kilobyte.

The required buffer size for selected data is 224230 bytes.

The fix: Adjusting the buffer size for optimal performance

To overcome this limitation, you can increase the buffer size within the system configuration. However, this change should initially be tested in a development environment to ensure it resolves the issue without causing other side effects. Follow these steps:

Step 1: Access the development environment

Start by implementing the fix in your Dev VM (development virtual machine) environment. Testing changes here allows you to confirm functionality and assess any impact on system performance.

Step 2: Run the buffer size adjustment script

The script below modifies the SYSGLOBALCONFIGURATION table, setting the buffer to a higher value. The script adjusts the VOLATILE_SQLTRANSFERBUFFERKBYTES setting, which controls the transfer buffer for SQL operations.

UPDATE SYSGLOBALCONFIGURATION
SET VALUE = 220
WHERE NAME = ‘VOLATILE_SQLTRANSFERBUFFERKBYTES’;

In this example, the buffer size is set to 220 KB, which should accommodate the record size required (224230 bytes). You can adjust this value further based on your specific data needs.

Step 3: Test and verify

After executing the script, attempt to load the problematic form to verify if the increased buffer resolves the issue. If the form loads correctly without errors, you can proceed to apply this solution to higher environments like UAT (User Acceptance Testing) and, eventually, production.

Moving to UAT and production

Once validated in Dev, the next step involves implementing the change in the UAT environment. You can access the UAT database through the Microsoft Dynamics Lifecycle Services (LCS) portal, which provides tools and utilities to manage your application environment.

If this adjustment is needed in the production environment, you can utilize the “Run custom X++ scripts with zero downtime” feature. This approach allows changes to be made without affecting active users or causing downtime. Be sure to calculate the buffer size accurately to avoid potential memory overloads, which could negatively impact performance.

Key considerations for performance tuning

When adjusting the buffer size, consider the following for better performance tuning:

• Impact on system performance: Increasing the buffer size can allow larger data sets to load, but excessive values can lead to memory strain. Adjust only as necessary to avoid unintended impacts on system performance.
• Testing in stages: Always start by testing in Dev, then move to UAT, and finally to production. Each stage provides an additional safeguard to catch potential issues before they reach the live environment.
• Continuous monitoring: After applying changes in production, monitor system performance for a period to ensure no new issues arise.

Summing up

With this solution, you can address this load issue with forms in Dynamics 365 effectively, restoring access to necessary data without compromising system stability. Be mindful of performance tuning principles, and always test thoroughly to ensure optimal results.

If you are facing this issue on production, you can execute this script by using the Run custom X++ scripts with zero downtime feature. In case you get stuck, feel free to reach out to us for support at marketing@confiz.com.

Note: Be careful when you are calculating the buffer size.