Microsoft Digital stories

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The choices we make today regarding technology platforms shape the success or failure of critical projects in the future.

For our Employee Productivity Engineering (EPE) team within Microsoft Digital, the company’s IT organization, the challenge of choosing between Microsoft Dataverse, our low-code data platform that is part of the Microsoft Power Platform, and Microsoft SQL Server, our relational database management system (RDBMS) used for storing and retrieving data as requested by other software applications, was more than a technical decision.

It was a balancing act between empowering business users, meeting operational demands, and aligning with our company’s strategic vision for scalable, secure, and high-performing solutions.

Faced with competing priorities, the EPE team embarked on a journey to evaluate these two powerful platforms, ultimately uncovering lessons and strategies that would guide their work and inspire our enterprise customers.

The Crossroads: Business needs and technical demands

The challenge of choosing between Dataverse and SQL Server wasn’t a simple one.

“Our project requirements pulled us in two very different directions,” says Urvi Sengar, a senior software engineer on the EPE team here in Microsoft Digital. “On one hand, we wanted the low-code, rapid development capabilities of Dataverse to empower business users. On the other hand, our backend demanded high-performance querying, advanced reporting, and seamless integration with other systems.”

The team’s decision wasn’t purely technical, it was rooted in six key dimensions: low-code development, security, extensibility, cost, governance, and performance. These considerations reflected the immediate needs of the projects and the long-term goals of enabling innovation while adhering to the company’s rigorous standards for compliance and scalability.

Mapping needs to capabilities

To navigate the complexity of the decision, the EPE team adopted a structured approach. They mapped their requirements across the six dimensions and evaluated Dataverse and SQL Server based on their unique strengths:

• Low-code development: Dataverse emerged as the clear winner for user-facing applications, thanks to its seamless integration with the Power Platform. Business users can use its low-code capabilities to build apps and automate workflows without relying heavily on engineering resources. The native connectors and templates further accelerate development timelines.
• Security and compliance: While both platforms offered robust controls, Dataverse’s role-based access and encryption—tightly integrated with the Microsoft cloud ecosystem—simplified compliance for business-centric apps. SQL Server, however, provided the granular control needed for systems handling sensitive or regulated data.
• Extensibility: The team found that Dataverse worked best for apps staying within the Power Platform ecosystem, while SQL Server excelled in complex backend operations and external integrations.
• Cost and governance: Dataverse’s licensing model was cost-effective for smaller-scale applications but became expensive at scale. SQL Server, with its mature governance models, offered predictable costs and reduced operational overhead when integrated into existing infrastructure.
• Performance and scalability: For data-intensive applications requiring real-time exports and complex joins, SQL Server’s ability to handle large datasets and optimize queries made it the superior choice.

The team didn’t rely on a single framework to evaluate the platforms—they blended the power of several tools together.

“We combined internal benchmarks, stakeholder interviews, and scenario-based analysis,” Sengar says. “The decision wasn’t binary—it was contextual, tailored to the unique needs of each project.”

Context-driven choices in action

The team’s thoughtful evaluation process came to life in two key projects, each showcasing the strengths of one platform over the other.

Dataverse was chosen as the data backbone for the Customer Validation Power App—a user-facing Power App designed to validate customer data. Its low-code capabilities and seamless integration with the Power Platform means that business users can use it to validate customer data, synchronize updates, and maintain compliance with Microsoft’s policies. They can also use the app to independently manage app features, which helps accelerate development cycles and reduce reliance on engineering resources.

“Dataverse is a game-changer for business-centric, low-code solutions, while SQL Server remains a cornerstone for high-performance, data-intensive applications.”

Urvi Sengar, senior software engineer, Microsoft Digital

In contrast, SQL Server proved indispensable for backend systems requiring high-performance querying and advanced analytics. By using SQL Server’s structured data control, computed columns, and user-defined functions, the team delivered real-time analytics and secure access management for sensitive data.

“SQL Server handled complex workloads with predictable performance, enabling us to integrate with external systems and legacy applications seamlessly,” Sengar says.

It came down to having to choose between two good options.

Looking ahead: A balanced approach to innovation

The EPE team’s work demonstrates the power of a contextual, thoughtful approach to technology selection. By understanding the strengths and trade-offs of both Dataverse and SQL Server, they not only delivered successful projects but also established a model for future decisions.

“The key takeaway for us was that the right choice depends on the specific context,” Sengar says. “Dataverse is a game-changer for business-centric, low-code solutions, while SQL Server remains a cornerstone for high-performance, data-intensive applications.”

As we continue to innovate here in Microsoft Digital and across the company, the lessons from our journey can serve as a guide for other teams navigating the complexities of platform decisions. By sharing their story, the EPE team hopes to inspire our enterprise customers to embrace a balanced approach to innovation, using the best of both worlds to achieve their goals.

Key takeaways

The EPE team’s journey revealed key lessons and best practices that other IT teams can apply:

• Context is everything: Dataverse and SQL Server serve different purposes, so your choice between the two should align with the specific needs of your application, user base, and operational goals.
• Don’t underestimate governance complexity: While Dataverse simplifies some aspects of governance, SQL Server offers granular controls that are critical for compliance-heavy systems.
• Integration isn’t always seamless: Testing real-time data flows early is essential to avoid surprises later, particularly when integrating Dataverse with external enterprise systems.
• Developer readiness matters: A successful transition to Dataverse requires investments in training and community engagement to ensure smooth adoption.
• Evaluate, align, and pilot: Among the best practices, Urvi highlights the importance of using a decision tree or framework to evaluate platform fit, aligning stakeholders early to surface hidden requirements, and running pilots before scaling to validate assumptions and uncover edge cases.

Try it out

• Get started with Dataverse and sign up for a free trial of Microsoft Copilot.
• Learn more about SQL Server 2025.

Related links

• Explore the Microsoft Dataverse documentation.
• Learn more about the Microsoft Power Platform.
• Explore educational SQL resources.
• Read more on SQL Server technical documentation.

The post How our team chose between Dataverse and SQL Server appeared first on Inside Track Blog.

When you’re responsible for processing over $500 billion in transactions every year, modernization becomes a mission-critical and highly delicate undertaking, where even the smallest misstep can carry serious financial consequences.

This was the challenge facing the Microsoft Treasury group, whose global operations relied on a patchwork of aging on-premises infrastructure, legacy systems, and leased lines.

Even the most mission-critical and entrenched systems must eventually evolve to meet the modern demands of speed, security, and scale.

“Modernizing the Treasury Service was not just about adopting new technology. It was about ensuring the uninterrupted operation of vital financial services while collaborating with various teams and meeting all security checks.”

Srinubabu Manikala, principal network engineering manager, Microsoft Digital

For Microsoft Treasury, that time had come—but instead of a straightforward infrastructure upgrade, the company seized the opportunity to go further.

What followed was a bold, strategic transformation that reinvented Microsoft Treasury’s core financial services, phasing out its aging infrastructure and migrating one of the world’s most complex treasury operations to the cloud.

“Modernizing the Treasury Service was not just about adopting new technology,” says Srinubabu Manikala, a principal network engineering manager in Microsoft Digital, the company’s IT organization. “It was about ensuring the uninterrupted operation of vital financial services while collaborating with various teams and meeting all security checks.”

A complex web of legacy, on-premises dependencies

Microsoft Treasury’s legacy infrastructure was initially built around a model where physical presence and dedicated hardware were the norm.

“The legacy network architecture was heavily dependent on on-premises infrastructure and leased lines from third-party partners. This introduced constraints, making the environment complex and difficult to scale.”

Harsh Shah, senior service engineer, Microsoft Digital

It supported a vast network of over 80 banking partners across more than 110 countries, enabling essential financial functions like bank guarantees, supply chain financing, ledger updates, and global cash visibility.

This infrastructure complexity made modernization a highly challenging, costly, and risky endeavor—especially with an architecture that relied heavily on leased lines, aging hardware, and on-premises access methods.

“The legacy network architecture was heavily dependent on on-premises infrastructure and leased lines from third-party partners,” says Harsh Shah, a senior service engineer for Microsoft Digital. “This introduced constraints, making the environment complex and difficult to scale.”

For instance, the “Trading Room” required traders to be on-site to access treasury systems, a model that was quickly disrupted during the COVID-19 pandemic. The growing need for secure remote access only intensified these pressures, especially as seamless integration with cloud-first partners became critical, and downtime was a non-starter. Even brief outages risked financial penalties and could disrupt transactions worth billions.

Navigating the challenge

The Microsoft Digital team responsible for overseeing Microsoft Treasury’s network infrastructure proposed two potential architectural solutions that would meet their modernization requirements while enhancing network infrastructure.

“Our partners in Treasury ultimately chose the second option, transitioning to a hybrid network. They have a long-term goal of moving entirely to the cloud using Azure.”

Justin Griffin, principal group network engineering manager, Microsoft Digital

The first solution involved refreshing all on-premises infrastructure and implementing robust measures to ensure continuity of services during the transition—a costly but safe bet.

The second, more ambitious solution called for a phased transition to a hybrid network with a long-term goal: go fully cloud-native using Microsoft Azure.

“Our partners in Treasury ultimately chose the second option, transitioning to a hybrid network,” says Justin Griffin, a principal group network engineering manager in Microsoft Digital, who led the team responsible for getting the project off the ground. “They have a long-term goal of moving entirely to the cloud using Azure.”

The decision was influenced by several factors, including the need to eliminate costly hardware and the desire for streamlined network management processes, including the use of Azure for seamless integration with internal and external systems.

Implementing the solution

With the second option chosen, the implementation goals were to eliminate on-premises hardware, cut costs, simplify management, and empower team members and partners to access Microsoft Treasury’s network from anywhere, securely. To this end, Azure would become the new backbone for Microsoft Treasury’s infrastructure.

The modernization effort centered around two cornerstone projects—the SWIFT Alliance SaaS migration and the migration of BlackRock’s Aladdin platform into Azure. The projects would leverage services like Azure VPN for secure remote access, Azure Firewall for enhanced protection, and Azure Virtual WAN (vWAN) for seamless global connectivity.

Modernizing the SWIFT integration

Microsoft Treasury relies on SWIFT for secure international payments. Previously, access to SWIFT required the use of on-premises hardware security modules (HSMs) for attestation and encryption.

The modernization efforts followed a phased migration path:

• Transitioning connectivity to Azure using vWAN and Site-to-Site VPNs
• Maintaining security by peering cloud networks with on-prem HSMs
• Eventually replacing on-premises HSMs with SWIFT’s SaaS-based attestation solution

The result was the retirement of leased lines and aging hardware, a reduced data center footprint, and cost savings of hundreds of thousands of dollars.

Aladdin secure remote access

To enable secure remote access to Aladdin—BlackRock’s investment management platform—Microsoft Digital collaborated with BlackRock and internal finance teams to implement a cloud-native Azure solution based on the following:

• Azure vWAN hubs with Point-to-Site VPNs for private user access
• Palo Alto Network virtual appliances for deep traffic monitoring
• BGP peering over IPsec for encrypted data transfers
• Geo-redundant routing for automatic failover in case of outages

Before the migration, outages caused by link failures, power surges, and WAN disruptions were not uncommon. But with the new infrastructure in place, Treasury Services users gained secure, uninterrupted access to Aladdin from anywhere. The move to the cloud, reinforced by availability zones and built-in high availability, effectively put an end to those disruptions.

A team effort: Reducing project risks and bolstering communications

During the transition, the Microsoft Digital team, the Treasury Services team, and their financial partners all played critical roles in executing a highly coordinated and technically demanding transformation.

To maintain continuity, the Treasury Services team temporarily increased its budget to support parallel operations across both the legacy on-premises environment and the new Azure-based infrastructure.

“We needed to make sure the communications were clear and acknowledged by each responsible individual to make sure no errors were made that compromised the availability of the system.”

Lionel Ramirez, senior technical program manager, Microsoft Digital Services

They also deployed new VPN clients to enable secure remote access and eventually migrated their HSMs handling critical SWIFT services to the SWIFT-hosted SaaS platform.

For financial partners, the migration meant shifting from traditional on-premises circuits to modern, cloud-based integrations with Azure. This required close collaboration across multiple internal and external teams. To support this shift, Microsoft Digital built a new Azure network infrastructure that integrated with legacy systems while laying the foundation for the fully cloud-hosted Treasury Services infrastructure.

“We needed to make sure the communications were clear and acknowledged by each responsible individual to make sure no errors were made that compromised the availability of the system,” says Lionel Ramirez, a senior technical program manager for Microsoft Digital Services.

Throughout the migration, the Microsoft Digital team ensured clear, continuous communication and required explicit acknowledgements for every critical step to minimize the risk of error and maintain service availability. All changes were carefully timed to occur after market hours and before trading activity resumed, further reducing the risk of disruption or financial penalties. The project team also adhered to stringent security and compliance requirements at every phase of the transition.

The results: Transformations that drive efficiency, security, and savings

By modernizing Microsoft Treasury Services’ network infrastructure—through migrating Aladdin to Azure and transitioning to SWIFT Alliance’s SaaS platform—the teams’ collaborative efforts achieved clear, measurable success

These initiatives boosted operational efficiency, strengthened security, and unlocked greater flexibility, all while bringing significantly reduced costs:

• Substantial cost savings: Over $1 million saved by eliminating the need for new network hardware and licenses.
• Enhanced operational continuity: Azure’s dynamic failover eliminated outages caused by power surges or link failures.
• Remote accessibility: Employees no longer need to be physically present in the Trading Room, with secure VPN access enabling global remote work.
• Greater scalability and agility: Treasury services can now scale in real time to meet evolving partner demands.
• Lower partner costs: Key financial partners like BlackRock were able to terminate expensive contracts for on-premises circuits, realizing further savings.
• Lower environmental footprint: A smaller data center footprint reduced energy consumption and maintenance overhead.

By using Azure’s powerful capabilities, Treasury Services is well-prepared to navigate the complexities of today’s financial landscape, ensuring resilience and agility in a rapidly evolving, dynamic environment.

Looking ahead

The modernization of Microsoft Treasury’s network infrastructure is a powerful example of what digital transformation can achieve. While the immediate gains—cost savings, improved reliability, and increased efficiency—were substantial, the true value lies in what this transformation made possible.

“The transition to a cloud-based network using Azure has empowered the Treasury team with the ability to scale efficiently in response to partner-related changes or enhancements, thanks to being fully hosted in the cloud.”

Justin Griffin, principal group network engineering manager, Microsoft Digital

By migrating to Azure and retiring legacy systems, the Treasury Services group, in partnership with the Microsoft Digital team, is now equipped to navigate the evolving financial landscape with greater agility, resilience, and confidence. The project not only addressed technical debt but also laid the groundwork for future innovation.

With a fully cloud-hosted treasury network, Treasury Services can more easily onboard new financial services and partners, scale operations on demand, and take full advantage of Azure’s built-in monitoring and security tools.

“The transition to a cloud-based network using Azure has empowered the Treasury team with the ability to scale efficiently in response to partner-related changes or enhancements, thanks to being fully hosted in the cloud,” Griffin says. “My team can now seamlessly adjust the Azure cloud network infrastructure to meet the Treasury team’s evolving demands and business needs.”

This success story also illustrates the impact of strategic collaboration, deliberate planning, and cutting-edge technology. It proves that even the most complex, deeply embedded financial systems—ones that move hundreds of billions of dollars—can be reinvented. What began as a high-stakes infrastructure challenge has become a model for future transformation.

Microsoft Treasury’s network infrastructure modernization isn’t just a technical achievement; it’s a blueprint for how organizations can evolve. The ultimate goal is a world where eliminating the legacy burden, embracing the cloud, and meeting high standards for speed, security, and scalability is the norm, not the exception.

Key takeaways

Here are some of our top insights from moving Microsoft Treasury Services network infrastructure to Azure:

• Embrace cloud migration as an achievable goal: Microsoft Treasury Services, in partnership with the Microsoft Digital team, overcame a significant IT challenge by transitioning from an on-premises system to a cloud-based network using Azure.
• Untangle complexity: Microsoft Treasury Services Azure, in partnership with the Microsoft Digital team, eliminated the need for on-premises hardware, significantly reducing system complexity and network maintenance requirements.
• Creating an adaptable partner ecosystem: In an environment where partners and providers increasingly operate in the cloud, the transition bolstered service continuity for critical financial functions and enabled remote access to financial services.
• Modernization saves time and money: The modernization resulted in substantial cost savings exceeding $1 million, and annual savings of approximately 200 hours in management time.
• Embrace migration challenges as opportunities: Microsoft Treasury Services looks forward to using Azure’s robust infrastructure to boost agility, cut costs, and fuel future innovation. Each opportunity to upgrade is a chance to innovate.

Try it out

• Sign up for a free trial of Microsoft Azure.
• Get started with Azure VWAN with routing intent and routing policies.

Related links

• Find out which five principles guided our move to the Azure cloud.
• Read about deploying global remote VWAN connectivity with Azure VWAN and Azure VPN.
• Explore our IT infrastructure journey to the cloud at Microsoft.
• Learn more about Azure Virtual WAN.
• Get more insights on how Azure VPN Gateways work.

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• Want more information? Email us and include a link to this story and we’ll get back to you.

The post The $500-billion challenge: Inside the modernization of Microsoft Treasury’s back-end infrastructure appeared first on Inside Track Blog.

Technology is constantly transforming the way we work—and AI is driving that evolution faster than ever. At Microsoft, the launch of Microsoft 365 Copilot is a powerful example of this shift.

However, launching an innovation of this scale inside the world’s largest software company came with its own set of challenges. The mission to embed Microsoft 365 Copilot into the fabric of our daily operations was spearheaded by Alexandra Jones, director of business programs, and Sandra Hausfelder, a global adoption lead for Copilot.

Together, the duo who work in Microsoft Digital, company’s IT organization, led a multi-disciplinary effort to ensure a smooth, impactful rollout—one that could serve as a blueprint for customers worldwide.

Jones, Hausfelder and their colleagues understood early on that rolling out Copilot and integrating it into the enterprise’s daily operations would require more than a one-size-fits-all approach.

“We have created a wealth of metrics and usage numbers in order to analyze the organizations, where employees are based, what their role is, and their current usage levels.”

Alexandra Jones, director of business programs, Microsoft Digital

Every team and role at Microsoft have unique needs, and the success of Copilot hinged on understanding and addressing those differences. Subsequently, the duo and their teammates worked with their IT colleagues across Microsoft Digital and partner teams from across the company to develop a change management and skilling strategy grounded in data and tailored by role and organization.

To ensure our adoption strategy was rooted in actionable insights, the team developed a robust data framework to understand user behavior across the organization. By analyzing factors such as geographic location, job function, and Copilot usage patterns, they surfaced high-value opportunities—what they referred to as adoption “hotspots,” or clusters of employees with shared roles and training needs.

Based on these adoption hotspots, they could design skilling activities for those specific groups, catering to their needs for more targeted and effective engagement.

“We have created a wealth of metrics and usage numbers in order to analyze the organizations, where employees are based, what their role is, and their current usage levels,” Jones says.

For example, one such hotspot identified was our Cloud Operations and Innovation (CO+I) organization, specifically employees in that organization working in data centers. The team designed targeted training events for these employees, using examples and skilling activities that resonated with their daily tasks and challenges. By mirroring real-world scenarios, Jones, Hausfelder and the team ensured that skilling felt relevant and immediately applicable—an approach that proved highly effective in driving usage.

From exploration to acceleration—building a culture of adoption

Hausfelder characterized the initial phase of Copilot deployment as a time of discovery and rapid learning.

“When I got engaged to drive adoption of Copilot at Microsoft, it was early days—some experiences were still basic, and all of us had to learn how to efficiently use it to support us,” Hausfelder says. “In fact, we were the first large, global enterprise to apply AI at scale. So initially we all were in a kind of explorer mode—discovering what it can do today, how we can bring all employees along on this journey, and how we can help envision the future of Copilot by collecting rich feedback.”

To support this journey, they launched an early adopters’ program, equipping engineers, support teams, and other strategic roles with Copilot licenses. As confidence and capability grew, the rollout expanded to include key areas such as legal, HR, marketing, and sales. Additionally, there were efforts to target employees working in specific roles, like change management, PM, software engineering, and so on.

Their multi-pronged enablement strategy included:

• Power hours: Guided sessions showing how to use Copilot across Microsoft 365 apps like Teams and Outlook.
• “Get Engaged” sessions: Interactive workshops—some hosted in local languages—to explore Copilot’s capabilities, gather live feedback, and surface feature requests.
• Surveys and analytics: Quantitative and qualitative feedback was gathered through in-app reporting, enterprise-wide surveys, and focused research activities.

These feedback loops weren’t just about fine-tuning internal adoption—they played a vital role in shaping the evolution of the product itself. User insights were prioritized and funneled directly to the Copilot product group, fueling a continuous improvement cycle.

Measuring success at scale and sustaining momentum

No transformation effort is complete without accountability.

“We could see exactly which organizations were thriving and where we had opportunities to re-engage.”

Sandra Hausfelder, a global Copilot adoption lead, Microsoft Digital

The team used Microsoft Viva to track progress and set measurable targets. Using aggregate data, they monitored monthly active usage—which consistently stayed in the 90% range—as well as net satisfaction (NSAT) scores, which offered insight into how users were responding to Copilot, and where there was room to improve.

This data allowed the team to pinpoint which change management strategies worked and where further engagement was needed.

“We could see exactly which organizations were thriving and where we had opportunities to re-engage,” Hausfelder says.

As Copilot continues to evolve, so does the need for ongoing learning and awareness. Features that may have underwhelmed users in the early days have since been enhanced—making it crucial to reintroduce them with a fresh perspective.

 “Copilot has completely changed the way I work,” Hausfelder says. “I’m excited to help others unlock the same kind of productivity gains—and to see where Copilot takes us next.”

To keep the momentum going without overwhelming users, we’re leveraging gamification, organic peer-to-peer learning, and an active internal community that shares role-specific use cases and favorite scenarios. We’re also expanding our Customer Zero efforts, identifying new “hero scenarios” that showcase transformative use cases and sharing those insights with both internal stakeholders and customers.

A playbook for the future of AI-assisted work

Our successful deployment of Copilot offers a pragmatic blueprint for organizations embarking on their own AI transformation. By grounding its strategy in data, tailoring adoption efforts to specific roles, and cultivating a culture of continuous feedback and exploration, As a company, we’re actively shaping the future of work—and setting a precedent others can learn from.

As Copilot evolves alongside the workforce, our approach highlights a practical reality—transformation isn’t a one-time milestone, but an ongoing journey of learning, adaptation, and innovation.

Key takeaways

Here are some top learnings you can adopt from our experience rolling out Copilot:

• Prepare for change: Accelerate the adoption of Copilot by designing a change management and skilling strategy based on organizations and roles.
• Meet people where they are: Identify groups of employees in specific roles and design skilling activities specific to their roles.
• Encourage ownership: Drive widespread adoption of Copilot by conducting sessions to engage employees and collect feedback.
• Measure the impact: Monitor usage and feedback to understand how Copilot is being used.
• Look ahead: As you deploy Copilot, stay alert to new opportunities for continuous learning, awareness, and productivity enhancement.

Try it out

• Experience the future of productivity with Microsoft 365 Copilot—your intelligent assistant for seamless work and collaboration.
• Discover the power of employee engagement and well-being with Microsoft Viva—transform your workplace today.

Related links

• Read our guide for deploying Microsoft 365 Copilot.
• Learn how we’re tackling Microsoft 365 Copilot governance internally at Microsoft.
• Find out how we’re unlocking the value of Microsoft 365 Copilot at Microsoft.
• Check out how we’re working to perfect Microsoft 365 Copilot localization.
• Discover how we’re deploying Copilot in Microsoft Viva Engage.

We’d like to hear from you!

• Want more information? Email us and include a link to this story and we’ll get back to you.

The post Driving the future of work: How we’re approaching Microsoft 365 Copilot change management at Microsoft appeared first on Inside Track Blog.

When a customer asked us if they should use Microsoft Copilot Studio or Microsoft Azure AI Foundry to build their employee self-service agent, we knew Ravi Goriparthy was exactly the right person to talk to.

He and the engineering team he works on here in Microsoft Digital, the company’s IT organization, had to answer that exact question when they set out to build agents that would help our Human Resources and IT Support teams better respond to requests for support from our employees.

We had Goriparthy, a principal software engineering manager, talk with our Inside Track bot, which wrote the following story (with some help from us humans).

Choosing the right platform

When it comes to solving complex IT challenges, the Human Resources Engineering team here in Microsoft Digital has a knack for navigating through the maze of available tools to find the optimal solution. As Goriparthy explains, their recent project to create an employee self-service agent for Microsoft employees and managers was no different.

The goal was ambitious: To build an intelligent agent that could answer questions about HR policies, offer IT help, and interact with various line of business (LoB) applications.

The challenge?

Deciding what combination of Microsoft 365 Copilot, Microsoft Copilot Studio, or Microsoft Azure AI Foundry would best serve their needs.

Understanding the landscape

Goriparthy and his team started to tackle the challenge by understanding the landscape of their LoB applications, focusing on policy content, help content, and employee data.

“We needed an agent that could easily integrate with a lot of LoB apps, as our data resides outside of the Microsoft 365 ecosystem,” Goriparthy says.

Their research led them to Copilot Studio, part of the Power Platform ecosystem, which offers more than 1,000 connectors to various LoB applications. The team created an agent using Copilot Studio, adding various SharePoint sites as knowledge sources. But there was a catch.

“We found that the agent was getting answers from various SharePoint sites that are not managed by the HR and IT business,” Goriparthy says.

The solution was to work with the Copilot Studio and Microsoft 365 Copilot teams to add an “authoritative source” badge to answers from configured SharePoint sites.

Driving integration

This wasn’t the end of their innovation. The team also integrated Copilot Studio with SuccessFactors and ServiceNow, identifying gaps in the existing Power Platform connectors and working with the respective engineering teams to enhance them.

“These integrations opened up numerous opportunities to improve employee productivity by providing an agent that can read employee data and take action on it, all from a single agent interface.”

Ravi Goriparthy, principal software engineering manager, Microsoft Digital

This included adding a metadata-driven extensibility design capability that anyone who deploys an employee self-service agent can use. This enabled our team to add metadata that reflects our SuccessFactors and ServiceNow customizations and that enables our Copilot actions to dynamically modify our API calls to get, update, and customize our datasets.

“These integrations opened up numerous opportunities to improve employee productivity by providing an agent that can read employee data and take action on it, all from a single agent interface,” Goriparthy says.

The project has since become a showcase of how agents can improve our employee experience and productivity, expanding the functionality of Microsoft 365 Copilot.

Goriparthy wants to help others navigate the AI landscape by sharing his team’s insights, providing clarity on when to use each tool—Microsoft 365 Copilot for enhancing productivity within the Microsoft 365 suite, Copilot Studio for creating custom AI agents and automating tasks, and Azure AI Foundry for developing and deploying custom AI applications.

Microsoft 365 Copilot is designed to enhance productivity within the suite of Microsoft 365 Copilot apps (Outlook, Teams, Word, etc.). Here are some common use cases:

• Document creation: Drafting documents in Word, creating presentations in PowerPoint, and analyzing data in Excel
• Email management: Summarizing emails, drafting responses, and organizing inboxes in Outlook
• Meetings: Generating meeting summaries, action items, and follow-up tasks in Teams
• Project management: Streamlining project planning and tracking progress in Planner
• Collaboration: Enhancing teamwork by integrating AI into SharePoint and OneDrive

Microsoft Copilot Studio is a low-code tool for creating custom AI agents and automating tasks. Typical use cases include:

• Customer support: Building agents to handle customer queries and provide support across multiple channels
• Employee assistance: Creating agents to answer common employee questions, manage benefits, and track public health information
• Custom solutions: Extending Microsoft 365 Copilot with your own enterprise data and scenarios
• Sales and marketing: Developing agents to assist with sales inquiries, to provide product information, and to support marketing campaigns

Microsoft Azure AI Studio is ideal for developing and deploying custom AI applications. Common use cases include:

• Generative AI: Creating applications that generate content, insights, and solutions from your data
• Predictive analytics: Building models to forecast trends, customer behavior, and market dynamics
• Natural language processing: Analyzing text data for sentiment analysis, customer feedback, and more
• Image and video analysis: Automating quality control, detecting anomalies, and enhancing security
• Custom AI solutions: Tailoring AI models to specific business needs across various industries

“You can use Microsoft 365 Copilot when you want to boost productivity and streamline tasks within the Microsoft 365 Copilot app ecosystem,” Goriparthy says. “Use Copilot Studio when you want to create custom AI agents and automate complex tasks with a low-code approach. And you should use Azure AI Studio when you need to build and deploy custom AI applications tailored to specific business needs.” 

Innovation, collaboration, and the pursuit of optimal solutions are at the heart of what Microsoft Digital does. As Goriparthy’s team has shown, embracing these values can lead to solutions that not only solve complex challenges but also propel the company and its customers into new frontiers of productivity and efficiency.

Key takeaways

Here are some tips for getting started with agents and Copilot Studio at your company:

• Evaluate needs and choose the right tools: Assess your organization’s requirements for an intelligent agent that can handle HR policies, IT help, and interact with various line of business (LoB) applications. Based on this assessment, decide between Microsoft 365 Copilot, Copilot Studio, and Azure AI Foundry, ensuring the chosen agent can easily integrate with multiple LoB applications, especially if your data resides outside the Microsoft 365 ecosystem.
• Configure knowledge sources: Add relevant SharePoint sites as knowledge sources for the agent, and work with the Copilot Studio and Microsoft 365 Copilot teams to add an “Authoritative Source” badge to answers from configured SharePoint sites.
• Enhance connectors: If you identify gaps in existing Power Platform connectors, you may need to build custom connectors to get them to integrate with your tools the way you want.
• Improve employee productivity: Use the integrated agent to read employee data and take actions on it to improve employee productivity from a single agent interface.
• Share insights: Share your team’s insights and experiences to help others navigate the AI landscape, providing clarity on when to use each tool for enhancing productivity, creating custom AI agents, and developing custom AI applications.

Try it out

Curious what Copilot Studio can accomplish for your business? Try a demo here.

Related links

• Learn how we’re boosting employee support at Microsoft with our new Employee Self-Service Agent.
• Unlock enterprise AI extensibility at Microsoft with Microsoft Copilot Studio.
• Use Microsoft 365 Copilot extensibility to unlock deeper AI value.
• Find out how our employees are extending enterprise AI with custom retrieval agents.
• See how we’re embracing this new ‘agentic’ moment at Microsoft.
• Learn more about the Inside Track content bot that wrote this story.

We’d like to hear from you!

• Want more information? Email us and include a link to this story and we’ll get back to you.

The post Customer questions answered: Should I use Copilot Studio or Azure AI Foundry to build my agent? appeared first on Inside Track Blog.

To stay ahead, we are continuously exploring ways to use technology to drive efficiency and value. One way we’re innovating is by using generative AI to accelerate content development for our Inside Track blog.

While there will always be humans in the loop, using generative AI, we have embarked on a journey to revolutionize how we engage with our customers through compelling stories and case studies. In fact, this very article was created with the help of Artificial Intelligence.

The vision and challenge

The vision for this project was clear: use AI to accelerate content creation, reduce turnaround times, and enable any member of our Microsoft Digital team to quickly share their story with customers. However, the path to realizing this vision was not without its challenges.

“We were venturing into uncharted territory, using AI in its infancy with a limited budget and few resources,” says Dwight D. Jones Sr., a principal product manager on the Frictionless Device team who led the initiative.

To overcome these challenges, the team created a pitch deck based on their vision, built a detailed technical specification, and worked with stakeholders to build support for the project. They formed a virtual team across the Microsoft Digital Inside Track team, the Frictionless Devices team, and the Employee Productivity Engineering team.

With the approval of Microsoft Digital leadership, they launched a small proof of concept that proved successful—the Inside Track content bot. In the pilot, the team was able to use an AI-powered interview bot to produce excellent first drafts of blog posts, saving significant time per story. 

Accelerating publication and reducing costs 

Senior Director Keith Boyd emphasized the dual challenge of telling more stories at a lower overall cost and accelerating publication.

“The key technology that’s powering the bot is OpenAI on Azure,” Boyd says. “It’s already helping us, by making it easier for subject matter experts in Microsoft Digital to share their expertise on their own schedule.” 

By using the bot, the team hopes to increase the number of stories in the pipeline and decrease the time it takes to reach publication.

“Our primary metric is time to publication,” Boyd says. “Can the bot help us move from a six-week cycle for story production to end-to-end story authoring and publication in half that time?” 

Streamlining the process 

Revanth Chandra Pydimarri, a senior product manager on the Inside Track content bot virtual team, highlighted the need to streamline the drafting and publishing process.

“We were wasting resources through inefficient operational processes, and it took a lot of time for us to reach out to relevant subject matter experts, get the content from them, write the story, and eventually publish it,” Pydimarri says. 

The team turned to Microsoft Azure AI, building a bot that uses generative AI capabilities—including Retrieval-augmented generation (RAG) and Azure OpenAI—on your data to interview subject matter experts (SMEs) at their convenience.

“We have trained the bot in the style of Inside Track,” Pydimarri says.

The results were impressive, with a time savings of at least five hours per story, while maintaining publication standards.

Capturing input and maintaining style 

Urvi Sengar focused on training the bot how to write stories with the same look and feel of human-written stories, and on how to use the bot to capture input from SMEs and turn it into content. The bot was trained using a comprehensive dataset of previously published stories and with writing guidance provided by the editorial team, enabling it to emulate the Inside Track team’s storytelling style.

 “The bot’s sophisticated content summarization and curation techniques allow it to draft high-quality stories quickly, maintaining the nuanced details and tone provided by the SMEs,” says Sengar, a senior software engineer in Microsoft Digital. 

Despite the challenges of transferring subject matter expertise and iteratively improving the process based on user feedback, the project has been well received by stakeholders.

“The bot is now able to generate drafts that are more than 70% complete, significantly reducing the time required to produce stories,” Sengar says.

The team is adding the ability for the bot to verbally interview SMEs by integrating VoiceRAG using Azure AI Search for audio to text capabilities. This will enable the bot to transcribe spoken interviews accurately and efficiently, streamlining the content collection phase and creating richer, multi-dimensional stories through a more natural interviewing process.

Combining multiple perspectives 

Lukas Velush, the managing editor of Inside Track, tackled the challenge of using an AI-powered bot to interview multiple SMEs and combine their interviews into one coherent story.

“Our challenge was to continue telling the stories of our subject matter experts across Microsoft Digital, despite having a smaller team and a shrinking budget,” Velush says.

This downward pressure on resources was the inspiration for the bot, which could help create stories at a lower cost and at a faster pace. 

The bot is designed to emulate human writers, interviewing SMEs about their IT work, their challenges, and how they overcame them.

“One of the biggest challenges that we’re still working on is getting the bot to be able to interview multiple people for a story then weave what each person has to say into a coherent narrative,” Velush says.

The current solution is having the bot interview each person separately, then combine the resulting stories into one comprehensive narrative. 

The initial results are promising, with bot-written stories costing 50% less than human-written stories and being completed at least 30% faster.

“This has been an amazing journey—we’ve learned a ton about AI, about humans, and about what it takes to report and write stories like this,” Velush says. “I see the bot as a great helper that can work right alongside our human writers.” 

The future of AI-driven content creation 

As Microsoft Digital continues to innovate and push boundaries, the Inside Track bot stands as a testament to the power of AI to transform the way we tell our stories. Using AI, the team has shown that it can accelerate the content creation process, enabling delivery of high-quality, engaging content faster and more efficiently than before. 

Looking ahead, the team plans to further enhance the bot’s capabilities. Jones shared that the team plans to use AI to produce multiple types of content with a single entry, such as articles, blog posts, PowerPoint decks, and white papers. They also plan to generate content in multiple languages and to support readers with accessibility needs. 

Boyd emphasized the potential for AI to augment human capabilities.

“One goal is to reassure other content teams that AI-powered bots are not here to replace them, but to augment their capabilities and make them more productive,” he says.

This is just the start.

“This is V1,” Pydimarri says. “We have plans to add more features and also expand the functionality to accommodate other team’s requirements, too.” 

Future enhancements will focus on expanding the bot’s capabilities and functionality. “That will ensure it continues to meet the evolving needs of the Inside Track team and other users,” Sengar says.

Looking to the future

Using AI to accelerate content creation in Microsoft Digital exemplifies the team’s innovative spirit and commitment to customer engagement.

“This project is just the beginning,” Jones says. “We’re excited about the potential of AI to revolutionize how we engage with our customers and look forward to seeing where this journey takes us.” 

The Inside Track bot has demonstrated the potential of AI to streamline processes, improve efficiency, and deliver high-quality, engaging stories that resonate with the audience. It’s a great example of digital transformation in action, paving the way for future innovations. 

As we continue to push the boundaries of what’s possible with AI, we invite you to join us on this journey. Explore the capabilities of the tools and technologies available through Microsoft Azure AI in your own content creation processes and see firsthand how it can enhance productivity and storytelling quality. 

We’re using AI to accelerate content generation at Microsoft, and you can too. Here are some highlights from our journey:

• AI-powered content creation: Microsoft Digital is using generative AI to automate content creation for the Inside Track blog, significantly reducing turnaround times.
• Successful pilot: The AI-powered chatbot proved successful in a pilot, producing excellent first drafts of blog posts and saving significant time per story.
• Efficiency and cost reduction: The initiative aims to tell more stories at a lower overall cost and accelerate publication, with Inside Track content bot-written stories costing 50% less and being completed at least 30% faster.
• Streamlined process: The AI bot interviews subject matter experts (SMEs) at their convenience, eliminating the need for coordinating schedules and saving at least five hours per story.
• Maintaining quality: The bot is trained to emulate the Inside Track team’s storytelling style, capturing nuanced details and tone provided by SMEs.
• Adding voice: We’re integrating Azure AI Speech Studio for audio-to-text capabilities, which will make getting interviewed by the Inside Track content bot a more natural experience for our SMEs.
• Future enhancements: We’re expanding the bot’s functionality to help other Microsoft Digital teams.

• Learn how to use Microsoft Azure OpenAI at your company.
• Learn more about Microsoft 365 Copilot.

• Read our guide for deploying and driving adoption of Microsoft 365 Copilot here at Microsoft.
• Find out how we’re tackling Microsoft 365 Copilot governance internally at Microsoft.
• Learn how we’re becoming an AI-first Frontier Firm.
• Check out how we’re embracing AI-powered agents internally here at Microsoft.

• Want more information? Email us and include a link to this story and we’ll get back to you.

The post Reimagining content creation with our Azure AI-powered Inside Track story bot appeared first on Inside Track Blog.

Just like it is for all large enterprises, maintaining accurate and secure group memberships enables our employees to collaborate effectively while also safeguarding our sensitive information internally here at Microsoft.

The Microsoft Group Membership Management (GMM) tool addresses this challenge head-on by providing a robust solution that simplifies group membership management while enhancing security and productivity across Microsoft. Initially developed to solve a challenge within Microsoft, GMM is now available on GitHub, giving other organizations to access to its capabilities.

The need for group membership management 

GMM was designed to address two critical issues that companies like ours face: 

• Collaboration barriers: When the right people aren’t in the group, collaboration tools are less effective.
• Security risks: When individuals retain access to groups unnecessarily, organizations face potential data exposure.

“One of our main priorities was to create a solution that balances seamless collaboration with stringent security,” adds Olivia Han, senior product manager for GMM. “We wanted organizations to feel confident in their group memberships while making the process as intuitive as possible.”

Key features of GMM 

GMM is a multi-source, multi-destination membership synchronization tool. It enables organizations to define group memberships based on user information from multiple sources and project those memberships into groups and even Microsoft Teams channels. Its standout features include: 

• Flexible membership definition: Membership can be defined based on organizational structure, user attributes, and exclusionary rules. Depth limits ensure precision and control. 
• Empowered group ownership: Group owners can define and manage their memberships independently, while administrators retain tools to protect sensitive HR information. 
• Change threshold protection: To prevent accidental disruptions, GMM includes increase and decrease thresholds that require owner confirmation before large-scale membership changes. 

Development journey and challenges 

GMM began as a solution to project nested security group hierarchies into flattened Microsoft 365 groups, addressing the lack of native nesting support in Microsoft 365. Over time, the tool evolved into a comprehensive solution that uses a variety of Azure services, including Storage, Service Bus, SQL, Azure Data Factory, and Key Vault, among others. 

“We’ve been laser-focused on adopting Microsoft Secure Future Initiative best practices,” says Paul Daly, a principal software engineering manager for GMM in Microsoft Digital. “Eliminating secrets, adopting managed identities, and moving resources to private networks have significantly improved our security posture. Scalability has been another ongoing focus, with innovations like a ‘multi-lane’ process to handle large membership changes without delays.” 

Impact and integration 

Internally at Microsoft, GMM has simplified maintenance for thousands of groups.

“Automating user additions increased the use of collaboration tools like Viva Engage, Teams, and Outlook groups,” Han says. “Removing unnecessary access not only boosts security but also gives us the confidence to enable features like Copilot.” 

GMM has had a significant impact on personalizing and enhancing the employee experience at Microsoft. By managing groups based on tenure, GMM enables targeted content delivery on the intranet website and HR portal via Viva Connections, providing relevant information to new employees during their crucial onboarding period. 

“Based on what our internal customers have told us, we know that GMM has eliminated days and even weeks of manual work that our business admins have to do to maintain accurate groups rosters,” Han says. “It has also mitigated security concerns, including reducing the risk of oversharing.” 

Externally, organizations that have adopted GMM from GitHub have experienced similar benefits, and their feedback has driven continued improvements. 

GMM integrates seamlessly with Entra ID groups and Team channel memberships, extending its impact across the Microsoft 365 suite, including Viva Engage, Teams, Outlook groups, Viva Connections, and CoPilot. 

Looking ahead 

The future of GMM is bright, with enhancements focused on usability, performance, and deployment: 

• Improved user interface: Updates driven by internal and external feedback reduce admin effort and empower users. 
• Enhanced scalability: The multi-lane process ensures timely completion of membership changes, even during large onboardings. 
• Simplified deployment: Streamlining installation will make GMM more accessible for external organizations. 

“We hope GMM’s features resonate with organizations and their use cases,” Daly says. “If so, we encourage them to give it a try and share their feedback via the GitHub repository.” 

GMM exemplifies how Microsoft uses its own tools to solve real-world challenges and shares those solutions to help others achieve their goals. With its powerful capabilities and user-centric design, GMM is transforming the way organizations manage group memberships, fostering both collaboration and security.

Here are some tips for rethinking group management at your company:

• Simplified group management: GMM streamlines group membership management, enhancing both security and productivity across organizations.
• Addressing key issues: GMM tackles collaboration barriers and security risks by ensuring that the right people are in the right groups and removing unnecessary access.
• Robust features: GMM offers flexible membership definitions, empowered group ownership, and change threshold protection to prevent accidental disruptions.
• Development and scalability: Initially created to solve internal challenges, GMM has evolved into a comprehensive solution using various Azure services and focusing on scalability and security.
• Impact and future enhancements: GMM has significantly improved group management at Microsoft with ongoing enhancements aimed at usability, performance, and deployment.

Learn more on how to manage your groups.

• Find additional resources for Group Membership Management on GitHub.
• Learn more about Group Membership Management (GMM).
• Unpack how Microsoft automates Group Member Management.

• Want more information? Email us and include a link to this story and we’ll get back to you.

The post Streamlining group membership management and governance at Microsoft appeared first on Inside Track Blog.

In the rapidly evolving world of cloud services, managing technical subscriptions can become a daunting task. At Microsoft, we faced a similar challenge—Microsoft Azure subscription sprawl.

“If customers don’t have a formal system in place to manage their Azure subscriptions, it can lead to subscription sprawl,” says Trey Morgan, a principal product manager on our Microsoft Digital Azure Optimization team. “This can cause potential legal and security risks.”

Our solution?

The Azure Information Request System (AIRS).

The impact of AIRS has been significant, particularly in governance and cost management. By assigning subscriptions to the business hierarchy from day one, they don’t get lost in a company of our size. We can quickly identify who to contact for security issues, cost issues, and understand how these cloud resources fit into Microsoft’s business.

— Trey Morgan, principal product manager, Microsoft Digital Azure Optimization team

AIRS streamlines the process of setting up new Azure subscriptions.

“AIRS is an internal system we’ve developed that offers a solution to govern and track subscriptions, a strategy that Microsoft has effectively used,” Morgan says.

Users requesting a new subscription fill out a form detailing cost assignment and ownership. The system also helps assign the subscription to our business hierarchy, providing visibility on where the cloud resources fit within the company.

“The impact of AIRS has been significant, particularly in governance and cost management,” Morgan says. “By assigning subscriptions to the business hierarchy from day one, they don’t get lost in a company of our size. We can quickly identify who to contact for security issues, cost issues, and understand how these cloud resources fit into Microsoft’s business.”

We’ve also integrated AIRS with tooling that benefits several different parts of our business.

“Azure governance, security, finance, and leadership all benefit from AIRS,” Morgan says. “Without it, we would lack crucial information about these Azure subscriptions or why they exist.”

Azure subscription sprawl strategies

To prevent subscription sprawl in your Azure environment, consider implementing the following strategies:

• Consistent landing zones: Establish consistent landing zones based on application archetype subscription strategies. This approach minimizes the growth of subscriptions by providing predefined structures for different types of workloads.
• Requisite components definition: Expand the definition of requisite components to better align with the governance and compliance needs of a mature cloud enterprise. Clearly define what components are necessary for each subscription, ensuring that they meet organizational standards.
• Subscription policies: Control the movement of Azure subscriptions out of the current directory and into it. Global administrators can allow or disallow users from changing the directory of an Azure subscription. For specific scenarios, configure a list of exempted users who can bypass the policy settings that apply to everyone else.
• Restrict self-service subscriptions: Disable self-service purchases to prevent standard users from creating subscriptions without proper authorization.

Remember that effective governance and clear policies play a crucial role in managing subscription sprawl and maintaining a well-organized Azure environment. As we continue to evolve and improve AIRS, we hope our journey can provide valuable insights for other companies navigating their own cloud subscription challenges.

The future of AIRS

Having a company operating model and policies is effective and IT leaders need to adhere to them and regularly review cloud subscriptions and usage to use them for the greatest security, flexibility, and output value. As we look to the future, we’re confident that AIRS will continue to evolve and provide even greater benefits to the company.

Consider using a system like AIRS to streamline the process of setting up new Azure subscriptions and assign them to the business hierarchy. Here are some tips on how you can get started at your company:

• Establish consistent landing zones based on application archetype subscription strategies to minimize the growth of subscriptions.
• Expand the definition of requisite components to align with the governance and compliance needs of a mature cloud enterprise.
• Control the movement of Azure subscriptions in and out of the current directory by setting subscription policies.
• Disable self-service purchases to prevent standard users from creating subscriptions without proper authorization.
• Remember that effective governance and clear policies play a crucial role in managing subscription sprawl and maintaining a well-organized Azure environment.

Create your Microsoft Azure free account today.

• Learn more about managing resources with Azure PowerShell.
• Unpack Azure Resource Manager in an overview.
• Discover revolutionizing SAP and ADP connectivity with Microsoft Azure VWAN and VPN.

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The post Creating a manageable Microsoft Azure subscription model appeared first on Inside Track Blog.