How software companies can expand their SMB reach with Microsoft Marketplace and AI
How can software companies turn a Microsoft Marketplace presence into greater customer reach and growth? Explore how Microsoft Marketplace can help software companies connect with more small and medium business (SMB) customers, support scalable sales, and expand into new markets in the age of AI. The article highlights Ntegral’s evolution from a traditional systems integrator to a software company with more than 300 enterprise solutions and deployments in more than 150 countries. You’ll also get a preview of what Ntegral President and CTO Dexter Hardy will bring to Ultimate Partner LIVE Reston, including practical perspectives on building beyond a Marketplace listing, developing pipeline, reaching SMB customers, and incorporating AI into a broader growth strategy. Read the full article to discover how Marketplace, AI-powered innovation, and an SMB-focused product strategy can work together to create new opportunities for software companies. 👉 Explore now: How software companies can reach more SMB customers through Microsoft Marketplace in the age of AICopilot, Microsoft 365 & Power Platform Community call
💡 Copilot, Microsoft 365 & Power Platform weekly community call focuses on different use cases and features within the Microsoft 365 and Power Platform - across Microsoft 365 Copilot, Copilot Studio, SharePoint, Power Apps and more. Demos in this call are presented by the community members. 👏 Looking to catch up on the latest news and updates, including cool community demos, this call is for you! 📅 On 15th of October we'll have following agenda: Latest on SharePoint Framework (SPFx) Latest on Copilot prompt of the week PnPjs CLI for Microsoft 365 Dev Proxy Reusable Controls for SPFx SPFx Toolkit VS Code extension PnP Search Solution Demos this time Richard Plantt – Getting Creative with SharePoint Dashboards Fabian Hutzli – Terraform for SharePoint Online: Declarative Site, List, and Tenant Management on Top of CLI for Microsoft 365 Carlos Miguel Silva – Awesome SharePoint Skills Factory 📅 Download recurrent invite from https://aka.ms/community/m365-powerplat-dev-call-invite 📞 & 📺 Join the Microsoft Teams meeting live at https://aka.ms/community/m365-powerplat-dev-call-join 💡 Building something cool for Microsoft 365 or Power Platform (Copilot, SharePoint, Power Apps, etc)? We are always looking for presenters - Volunteer for a community call demo at https://aka.ms/community/request/demo 👋 See you in the call! 📖 Resources: Previous community call recordings and demos from the Microsoft Community Learning YouTube channel at https://aka.ms/community/youtube Microsoft 365 & Power Platform samples from Microsoft and community - https://aka.ms/community/samples Microsoft 365 & Power Platform community details - https://aka.ms/community/home 🧡 Sharing is caring!Copilot Extensibility community call - October 2026
🚀 The Copilot Extensibility Monthly Community Call is a recurring virtual gathering designed to keep the global developer and maker community consistently connected, informed, and engaged with the latest advancements in Microsoft 365 Copilot, Copilot Cowork, Microsoft Scout, GitHub Copilot, Microsoft IQ, etc. and their extensibility ecosystem. 👏 Monthly Wednesday call is for all community members to see Microsoft PMs, engineering and Cloud Advocates showcasing the art of possible with the Microsoft AI technologies. 📅 On the 14th of October we'll have following agenda: News and updates from Microsoft Community group photo Dona Sarkar – Introducing the new Copilot with Home, Code and Autopilot Sai Deepthi Kovvuru - Evaluate your M365 Copilot agents with natural language Rabia Williams - Shipping One Plugin to Cowork and Copilot with Work IQ 📞 & 📺 Join the Microsoft Teams meeting live at https://aka.ms/community/CopilotExtensibility-call-join 🗓️ Download recurrent invite for this weekly call from https://aka.ms/community/CopilotExtensibility-call-invite 👋 See you in the call! 💡 Building something cool with Microsoft AI technologies (Copilot, Cowork, Copilot Studio, Microsoft IQ, etc)? We are always looking for presenters - Volunteer for a community call demo at https://aka.ms/community/request/demo 📖 Resources: Previous community call recordings and demos from the Microsoft Community Learning YouTube channel at https://aka.ms/community/youtube Labs and training material about Microsoft 365 Copilot Extensibility - https://aka.ms/copilotdevcamp Microsoft 365 & Power Platform samples from Microsoft and community - https://aka.ms/community/samples Microsoft 365 & Power Platform community details - https://aka.ms/community/home 🧡 Sharing is caring!Copilot, Microsoft 365 & Power Platform product updates call
💡Copilot, Microsoft 365 & Power Platform product updates call concentrates on the different use cases and features within the Microsoft 365 and in Power Platform. Call includes topics like Microsoft 365 Copilot, Copilot Studio, Microsoft Teams, Power Platform, Microsoft Graph, Microsoft Viva, Microsoft Search, Microsoft Lists, SharePoint, Power Automate, Power Apps and more. 👏 Weekly Tuesday call is for all community members to see Microsoft PMs, engineering and Cloud Advocates showcasing the art of possible with Microsoft 365 and Power Platform. 📅 On the 13th of October we'll have following agenda: News and updates from Microsoft Together mode group photo Vid Chari – End to end business process transformation with apps, agents and workflows AI in Copilot Studio Joe Komban – Creating Personal Skills to capture your way of working and portability across SharePoint Steve Pucelik – Advanced file management and security in SharePoint Embedded 📞 & 📺 Join the Microsoft Teams meeting live at https://aka.ms/community/ms-speakers-call-join 🗓️ Download recurrent invite for this weekly call from https://aka.ms/community/ms-speakers-call-invite 👋 See you in the call! 💡 Building something cool for Microsoft 365 or Power Platform (Copilot, SharePoint, Power Apps, etc)? We are always looking for presenters - Volunteer for a community call demo at https://aka.ms/community/request/demo 📖 Resources: Previous community call recordings and demos from the Microsoft Community Learning YouTube channel at https://aka.ms/community/youtube Microsoft 365 & Power Platform samples from Microsoft and community - https://aka.ms/community/samples Microsoft 365 & Power Platform community details - https://aka.ms/community/home 🧡 Sharing is caring!New Microsoft 365 Certified: AI Services Administrator Associate Certification
As AI moves deeper into mission-critical work, organizations need trusted administrators who can govern access, secure data, monitor services, and keep Microsoft 365 AI experiences running at enterprise scale. Show you’re ready with new Exam AB-650 (beta). AI-powered productivity is no longer just about enabling new capabilities, it’s about operating them with the right controls, safeguards, and visibility. Organizations need administrators who can help make Microsoft 365, Microsoft 365 Copilot, agents, and connected AI services secure, compliant, reliable, and scalable across the enterprise. The new Microsoft 365 Certified: AI Services Administrator Associate Certification validates the skills to configure, manage, secure, govern, and continuously optimize Microsoft 365 tenants, workloads, and AI services so organizations can adopt AI with confidence and drive effective outcomes at scale. To earn this Microsoft Certification, you’ll need to pass Exam AB-650: Administering Microsoft 365 and AI Services, currently in beta. Is this the right Certification for you? Candidates for this Certification: Configure, manage, secure, and govern Microsoft 365 tenants, workloads, and AI services, including Copilot, agents, and connected AI capabilities. Govern data access, protect information, and support collaboration between users and agents. Operate and continuously optimize Microsoft 365 and AI services at enterprise scale, helping to ensure reliable and effective outcomes in an AI-powered workplace. Candidates should have experience with Microsoft 365 workloads and Microsoft Entra ID, an understanding of Defender XDR capabilities, and familiarity with Microsoft Graph PowerShell. Ready to prove your skills? Take advantage of the discounted beta exam offer. The first 300 people who take Exam AB-650 (beta) on or before August 18, 2026, can get 80% off. To receive the discount, when you register for the exam and are prompted for payment, use code AB-650SkyClub . This is not a private access code. The seats are offered on a first-come, first-served basis. As noted, you must take the exam on or before August 18, 2026. Please note that this discount is not available in Turkey, Pakistan, India, or China. How to prepare Get ready to take Exam AB-650 (beta): Review the Exam AB-650 (beta) page for training resources, exam registration, and other details. The Exam AB-650 study guide explores key topics covered in the exam. Connect with Microsoft Training Services Partners in your area for in-person offerings. Need other preparation ideas? Check out Just How Does One Prepare for Beta Exams? Ready to get started? You can take Certification exams online, from your home or office. Get the details in Online proctored exams: What to expect and how to prepare. Remember, only the first 300 candidates can get 80% off Exam AB-650 (beta) with code AB-650SkyClub on or before August 18, 2026. Beta exam rescoring begins when the exam goes live, with final results released approximately 10 days later. For more details, read Creating high-quality exams: The path from beta to live. Stay tuned for general availability of this Certification in October 2026. Additional information For more Certification updates, read our recent blog post, Microsoft Credentials roundup: June 2026. Follow our credentials news on The Skills Hub Blog as we roll out additional new Certifications in August and September 2026. Join our Microsoft Worldwide Learning SME Group for Credentials on LinkedIn for beta exam alerts and opportunities to help shape future Microsoft learning and assessments. Explore Microsoft Credentials on AI Skills Navigator.Syksyn 2026 Tekniset ja myynnin Kumppanitunnit
Microsoftin tekniset ja myynnille suunnatut Kumppanitunnit järjestetään nykyään Microsoftin globaalilla Skilling Hub -sivustolla, josta ne ovat kätevästi saatavilla myöhemmin tallenteina materiaaleineen. Rekisteröidy Skilling Hub -portaaliin, josta löydät kaikki Microsoftin kumppanikoulutukset yhdessä paikassa eri kielillä tai tekstitettyinä. Rekisteröityessäsi voi valita ne kielet, kuten suomi, jollaista sisältöä haluat ensisijaisesti nähdä englannin kielisen koulutussisällön lisäksi. Kumppanitunti on joka toinen perjantai klo 10–11 järjestettävä Microsoftin kumppaniwebinaari, joka on tarkoitettu kaikille Microsoftin kumppaneille. Tekniset ja kaupalliset aiheet vuorottelevat ja olet tervetullut molempiin webinaareihin. Webinaareissa keskitymme Microsoftin ratkaisualueiden teknologioiden mielenkiintoisiin uutuuksiin, MAICPP-kumppaniohjelmaan, kumppanietuihin ja ratkaisumyyntiin. Microsoftin suomalaiset arkkitehdit, tuotepäälliköt, ratkaisumyyjät ja kumppanivastaavat ovat poimineet kiinnostavia ja hyödyllisiä aiheita, joita he vuorollaan esittelevät. Syksyn 2026 ohjelma Alla ovat suunnitellut päivät ja teemat Syksylle 2026, joiden tarkka aihe päivitetään aina lähempänä esityspäivää tälle sivulle. 18.9. Kaupallinen Kumppanitunti: Partner START FY27 - webinaari Katso tallenne tästä linkistä: Etkö päässyt mukaan START FY27 Kickoff -tapahtumaan? Webinaarissa saat kattavan katsauksen tapahtumassa käsiteltyihin FY27: n liiketoimintamahdollisuuksiin, strategisiin painopisteisiin sekä Microsoftin kumppaneille suunnattuihin ohjelmiin ja resursseihin. Puhujat: Kalle Saarikannas, Liiketoimintajohtaja, AI Business Solutions Teemu Lainiola, Liiketoimintajohtaja, Cloud & AI Platforms Mereta Laukkanen, Sr Partner Development Manager Jonna Kaarlenkaski, Partner Development Manager Intern Jonna Fred-Jokela, Sr Solution Engineer Manager 2.10. Tekninen Kumppanitunti: Copilot Cowork: Copilot Credits ja kustannusten hallinta Katso tallenne tästä linkistä! Tässä teknisessä kumppanitunnissa käymme läpi Copilot Coworkin toimintamallin, kulutuksen seurannan sekä kustannusten hallinnan. Lisäksi tarkastelemme, millaisia mahdollisuuksia kulutuspohjainen AI luo kumppaneiden palveluliiketoiminnalle. Puhujat: Henri Nevalainen, Microsoft Niko Hiltunen, IAMCP 9.10. Kaupallinen Kumppanitunti: Onko julkisen pilven suvereniteetti riittävä huomioiden sen kaikki hyödyt? Rekisteröidy mukaan tästä linkistä! Euroopan unioni valmistelee uusia pilvi- ja tekoälyinfrastruktuuria koskevia linjauksia. Samanaikaisesti organisaatiot pohtivat, miten digitaalinen suvereniteetti, tekoälyn käyttöönotto, kyberturvallisuus ja sääntelyvaatimukset voidaan sovittaa yhteen käytännössä. Tervetuloa ajankohtaiseen webinaariin, jossa tarkastelemme Euroopan muuttuvaa pilviympäristöä ja mitä digitaalinen suvereniteetti tarkoittaa suomalaisille organisaatioille käytännössä. Lisäksi kerromme viimeisimmät tilannetiedot pilvipalveluiden kvanttiturvallisuuden ja Suomen datakeskushankkeiden osalta. Puhujat: Juha Karppinen, National Technology Officer, Microsoft Timo Salminen, Partner Solution Architect, Microsoft Niko Hiltunen, IAMCP 22.10. Kaupallinen Kumppanitunti: Frontier Transformation - Next level IQ & Uusi näkökulma kumppanin rooliin AI-aikakaudella Rekisteröitymislinkki päivittyy tähän AI-transformaatio on siirtymässä yksittäisten työkalujen käyttöönotosta kohti laajempaa työn ja toimintamallien uudistamista. Kumppanitunnilla havainnollistamme käytännön esimerkin avulla, kuinka organisaation toimintaa voidaan tarkastella digitaalisen genomin kautta, organisaatiosta ja tiedosta aina työhön, mikrotehtäviin ja agentteihin asti. Samalla tarkastelemme, mitä muutos tarkoittaa kumppaneille: miten tunnistaa uusia asiakasarvon mahdollisuuksia, rakentaa vaikuttavampia AI-keskusteluja ja auttaa asiakkaita etenemään kohti agenttipohjaista toimintamallia. Tule mukaan katsomaan demo ja pohtimaan, mitä seuraavan vaiheen AI-transformaatio mahdollistaa sinun asiakkaillesi. Puhujat: Hans Dolk, Asiakkuusjohtaja / Defence & Intelligence, Public Safety and National Security Juha Liljeblom,Teknologia Strategisti / Defence & Intelligence, Public Safety and National Security 23.10. Kaupallinen Kumppanitunti: Uudistunut Microsoft Copilot: ominaisuudet, käyttötavat ja kustannusten hallinta Rekisteröidy mukaan tästä linkistä! Microsoft Copilot uudistuu merkittävästi. Copilotista rakentuu paikka, jossa käyttäjä voi kysyä, delegoida, rakentaa ja automatisoida työtä. Uudet Home-, Code- ja Autopilot-kokemukset laajentavat Copilotin käyttöä päivittäisestä AI-avustamisesta kohti pidempikestoista agenttityötä ja käyttäjien itse rakentamia ratkaisuja. Webinaarin tavoitteena on antaa kumppaneille selkeä kokonaiskuva siitä, miten uudistunut Copilot muuttaa asiakkaiden AI:n käyttötapoja, lisensointi- ja kulutuskeskustelua sekä kumppaneille avautuvia mahdollisuuksia. Puhujat: Harri Mikkanen, Microsoft Tuulia Piehl, Microsoft Henri Nevalainen, Microsoft 30.10. Tekninen Kumppanitunti: Rekisteröitymislinkki päivittyy tähän Puhujat: 6.11. Tekninen Kumppanitunti: Rekisteröitymislinkki päivittyy tähän Puhujat: 20.11. Kaupallinen Kumppanitunti: Rekisteröitymislinkki päivittyy tähän Puhujat: 4.12. Kaupallinen Kumppanitunti: Rekisteröitymislinkki päivittyy tähän Puhujat: 18.12. Tekninen Kumppanitunti: Agentit Azuressa Rekisteröitymislinkki päivittyy tähän Azure Copilot pitää sisällään uusia palveluiden elinkaarenhallintaan liittyviä agentteja. Tule kuulemaan, miten voit hyödyntää näitä omissa palveluissasi! Puhujat: Timo Salminen, Partner Solution Architect, MicrosoftAI-powered + human-focused: Powering workforce transformation
How Microsoft combines the reach and personalization of AI with human expertise to turn workforce learning into business impact. When we think about AI transformation, we have to start with employees. There is simply no way around it. You can deploy the technology and set ambitious goals, but if people do not have the confidence, skills, and support to use AI in their work, transformation will not happen. Employees are the ones who turn AI from an experiment into real business impact. Microsoft’s skilling approach brings together two complementary ideas: AI-powered skilling and human-focused learning. AI-powered experiences extend reach, personalization, and access. Human-focused experiences provide context, trust, dialogue, and connection. The point is not to choose between AI and people. It’s to combine their strengths in a portfolio that can meet different workforce needs, organizational goals, levels of readiness, and learning preferences. AI-powered learning experiences AI can make skilling more personal, relevant, and continuous. It can help employees identify the right place to start, shape learning around their roles and goals, adapt content to different needs and preferences, and provide support as they build and apply new skills. For organizations, AI makes it possible to guide learning at scale, align development with workforce priorities, and understand progress over time. AI Skills Navigator brings these capabilities together in one connected, AI-powered skilling experience for individuals and organizations. Learning shaped around individual and team needs Employees bring different goals and levels of experience to learning. AI Skills Navigator can help meet those differences at scale: employees can use AI to create skilling playlists around their own goals, while team leaders can create playlists tailored to their teams’ needs. In skilling sessions, an AI-powered coach can answer employees’ questions, help them work through concepts, and reinforce understanding with knowledge checks. Together, these experiences help organizations provide trusted, relevant learning while supporting each employee’s progress. Relevant skilling across roles The AI skills needed to lead, market, sell, build, secure, or manage technology are different. AI Skills Navigator supports roles across the organization with ready-to-use featured playlists curated by Microsoft around roles, topics, or outcomes. AI-generated podcasts and summaries also let employees transform written content into new modalities to easily revisit key ideas in a format that fits their preferences and available time—making role-relevant learning easier to access across the workforce. Guiding and measuring workforce skilling Organizations need more than access to learning. AI Skills Navigator enables leaders to assign skilling playlists across teams, business groups, or the entire company and track progress over time. Organizational reporting provides visibility into participation, playlist adoption, progress, popular content, and the skills employees are developing. These insights help leaders understand engagement, reinforce workforce priorities, and focus continued development where it matters most. Human skill building and delivery AI transformation demands more than technical skills. We pair technical and role-based skilling with enduring human capabilities such as curiosity, courage, compassion, creativity, collaboration, and judgment. These capabilities help employees ask better questions, navigate ambiguity, make responsible decisions, collaborate effectively, and adapt as roles evolve. Human-led learning reinforces them through context, dialogue, practice, and connection—experiences that complement the reach and personalization of AI-powered learning and prepare people not only to use AI tools, but to exercise judgment, adapt their work, and thrive as roles continue to evolve. Microsoft offers scalable skilling solutions designed to meet the needs of organizations at every stage of their AI transformation. In select situations where deeper support can accelerate progress, Microsoft works directly with customers on tailored skilling plans and private onsite or virtual delivery, combining role-based learning with human expertise, context, and practice to help teams move from AI intent to confident execution. One portfolio, two complementary approaches AI-powered and human-focused learning solve different parts of the same workforce challenge. AI-powered experiences make learning easier to personalize, discover, and scale. Human-focused experiences add the expertise, trust, context, and connection that people need to turn knowledge into confident action. Organizations can use on-demand, AI-led learning where flexibility and reach matter most, then add human-led delivery where deeper context, practice, or alignment is needed. The mix can vary by role, population, initiative, and stage of readiness. The next step: Explore AI Skills Navigator to find role-based learning, build a path that fits your goals, and start developing the skills to turn AI into impact—one skill at a time.When the Answer Isn’t in the Document: Metadata-Aware Agentic RAG with Foundry IQ
The problem SharePoint libraries often contain years of carefully curated metadata, including root cause, severity, business unit, document type, owner and classification. If that metadata never reaches the retrieval pipeline, however, a RAG system cannot use it. This creates a common blind spot: the information that explains what a document is about may exist in its metadata rather than its text. Consider an incident review containing this statement: “Investigation found that a DNS record was repointed during a migration while the old target was still serving writes.” The associated Root Cause Category is Configuration change, but those words do not appear in the document. Another review might mention that a configuration change was suspected and ruled out. Text-only retrieval can therefore favour the wrong document. In the sample dataset used for this project, none of the 19 reviews classified as configuration-change incidents contained the word “configuration”, while six reviews with other root causes did. Metadata does not improve every search. It helps when the information that determines what a document is lives outside the document text. Why tuning alone cannot fix it With a native SharePoint knowledge source, document text is extracted, chunked and embedded, while standard properties are retained. Custom SharePoint columns are not part of that ingestion path. Fields such as Root Cause Category, Contributing Factors, Detection Method and Severity therefore never become structured fields available to retrieval. If the metadata is absent from the index, search tuning cannot make it count. Flattening all metadata into a single text string is also problematic: Notification Service | Sev2 | Configuration change | Missing runbook This preserves the words but loses their meaning. A root cause, severity and contributing factor represent different concepts and should remain separate fields. Bring a custom Azure AI Search index The approach is to create and control a custom Azure AI Search index, then expose it to Foundry IQ as a searchIndex knowledge source. This combines metadata control with agentic query planning and a governed retrieval surface. Approach Metadata control Agentic planning Native SharePoint knowledge source No Yes Custom index queried directly Yes No Custom index as a knowledge source Yes Yes Architecture The key design principle is simple: every chunk carries its parent document's metadata. Figure 1. Metadata-aware retrieval architecture with Azure AI Search and Foundry IQ. The ingestion pipeline extracts a document, creates chunks, attaches document-level metadata to every chunk, generates embeddings and writes the records to Azure AI Search. Foundry IQ then uses the index as a knowledge source. Azure AI Search holds the metadata. Foundry IQ decides when to use it. Figure 2. Detailed implementation view, including the baseline and metadata-aware retrieval paths. At query time, the search service calls the configured models for vectorisation and query planning. Where key authentication is disabled, the search service's managed identity needs the required access. In the tested implementation, the Cognitive Services User role resolved HTTP 401 responses from retrieve requests. Put metadata on every chunk A chunk can only be retrieved and ranked using information available on that chunk. Each metadata property should therefore remain in its own field: { "id": "doc1035-000", "parentId": "doc1035", "title": "Notification Service: failed sign-ins", "content": "<extracted review text>", "rootCauseCategory": "Configuration change", "contributingFactors": "Missing runbook; Change outside window", "detectionMethod": "Customer report", "severity": "Sev2" } A separate metadata index does not solve the same problem because a match against metadata in one index cannot raise the ranking of a content chunk in another. What influences retrieval Four areas matter in this design: Search fields: searchFields determine which fields generated subqueries search. Semantic configuration: prioritised fields give the semantic reranker access to important metadata. Query hints: hints help the planner connect natural-language requests to known metadata values. Filters: a baseFilter or request-level filterAddOn can enforce constraints. Boost hints influence ranking without excluding documents. Filter hints can narrow the result set when the planner determines that a filter is appropriate. "queryHints": { "boosts": [{ "kind": "fieldValue", "field": "rootCauseCategory", "fieldValues": ["Configuration change", "Capacity", "Software defect", "Dependency failure", "Certificate expiry"], "boost": 3.0, "boostInstructions": "Boost when the user describes what caused an incident." }] } Hints are best effort. Hard requirements should use a base filter or document-level access control rather than relying on the planner to select a hint. The tested configuration used the 2026-08-01-preview API. Current documentation should be checked for supported models, limits and behaviour before implementation. Measuring the impact Two knowledge bases were created over the same Azure AI Search index. The baseline searched title and content. The metadata-aware configuration used the same content plus structured metadata, semantic configuration and query hints. Ten questions were run through both configurations. Correctness was determined directly from the metadata attached to returned reviews, rather than by asking an LLM whether a result appeared relevant. For the question “What can be learned from outages caused by configuration changes?”, the planner generated: rootCauseCategory eq 'Configuration change' Matching reports in top 5 Score Baseline 0 Metadata-aware 3 Best possible 5 Across ten questions and four runs using gpt-5.4-mini for query planning, the baseline returned 26 matching reviews in the top five. The metadata-aware configuration returned 39 to 41, against a best possible score of 50. The gains appeared where metadata carried the missing meaning: Configuration changes: 0 → 3 Configuration changes reported by customers: 0 → 3 Capacity in production: 1 → 5 Alert fatigue: 3 → 5 Queries whose important terms already appeared in the document text scored 5/5 in both configurations. The result is therefore more specific than “metadata improves search”: metadata closes a retrieval gap when document text does not fully describe what the document represents. A failure mode worth handling Because query planning uses an LLM, the planner can occasionally generate a filter that the search index rejects. Two invalid examples observed during testing were: severity eq Sev1 changeRelated eq true The first omitted quotes around a string. The second treated an Edm.String field containing Yes and No as a Boolean. The latter caused the retrieve request to fail with HTTP 502. The fix was to make the schema and allowed values explicit: This is a text field, not a Boolean. The only valid values are 'Yes' and 'No'. Never compare the field with true or false. Application code should also handle retrieval failures rather than assuming every generated filter will be valid. Production considerations A custom index provides control, but the solution now owns ingestion. Options include the SharePoint indexer with custom columns, an Azure Function using Microsoft Graph, or an existing pipeline built with Logic Apps, Azure Data Factory or Microsoft Fabric. A custom Azure AI Search index does not automatically inherit the SharePoint permissions model. Where users have different document permissions, ACLs must be carried into ingestion and retrieval. Query hints should also be regenerated when taxonomy values change. Key takeaways Confirm that the required metadata reaches the index. Keep metadata structured rather than flattening it into one text field. Attach parent-document metadata to every chunk. Use search fields, semantic configuration, query hints and filters deliberately. Describe field types and valid values clearly in filter instructions. Evaluate against a baseline using objective correctness rules. Metadata-aware retrieval is not about making every search better. It gives the retrieval system access to context that does not exist in the document text. Try the proof of concept The complete proof of concept, synthetic dataset, index scripts, knowledge-base configurations and A/B evaluation harness are available in the GitHub - shikha-msft/foundryiq-metadata-agentic-rag. References Create a search index knowledge source Create a knowledge base Query a knowledge base via API or MCP What is Foundry IQ?💲Announcing Free Grant and Pricing for Logic Apps Automation
Today, we're announcing pricing for Azure Logic Apps Automation, now in public preview, along with monthly free grants that make it easier to start building, experimenting, and bringing automations to life. Logic Apps Automation is Azure's fully managed platform for business process automation and orchestration, including AI-powered automation. It's built for every builder with an automation problem, not just developers, and the free grants make it easy to go from idea to a working automation without a purchase decision up front. The free grant covers one managed environment per subscription and includes usage across key Logic Apps Automation capabilities, so you can start with your first use case, experiment with AI-powered automation, and run workloads in production within the included limits; then move to paid usage as your needs grow. Start today @ https://auto.azure.com/ Start free with monthly grants Every Azure subscription gets a monthly free grant across the platform. The only exception is Managed Environment which is a one-time free grant for first 60 days. When the usage stays within these limits you pay nothing. When it goes beyond these limits, you pay only for the additional usage. Usage Component Monthly free grant (per subscription) Core Platform Managed environment One environment, free for the first 60 days (2 months) Core Platform Workflow runtime 108,000 execution-seconds (about 30 hours) Core Platform Data retention 1 GB Optional Capabilities Managed connector calls 1,000 Standard + 500 Enterprise Optional Capabilities Knowledge storage 1 GB Optional Capabilities AI usage 1,100 AACs Optional Capabilities Isolated code execution 18,000 seconds (about 5 hours) What this means in practice Explore the platform, not a trimmed-down experience. The grants include workflow runtime, AI usage, knowledge, connectors, and sandboxed code, so you can explore every capability from day one. Build and iterate without watching the meter. With approximately 30 hours of execution time included each month, you can author, test, and run workflows as you build out your automation. Scale into paid usage as your needs grow. Grants reset every month, and you pay only for usage beyond them. Simple, usage-based pricing Beyond the included grants, Logic Apps Automation uses a pay-as-you-go pricing model across the capabilities your automations use. Billing has two parts: Core Platform: the managed environment, workflow runtime, and run-history retention that provide the foundation for your automations. Optional Capabilities: AI usage, knowledge storage, isolated code execution via sandbox and managed connectors, billed only when your workflows use them. For rates, regional pricing, and a worked monthly cost example, see Azure Logic Apps Automation pricing. How does the free grant works The free grant applies to the first environment you create in a subscription. Look for the Free tag next to an environment's name to see which is the free one Free environment period: The managed environment is free for 60 days, starting from the time you create it. Existing customers: If you already use Logic Apps Automation, create a new environment to use the free grant. The first new environment you create in your subscription receives it. Track your usage: In your environment, go to Settings and select the Free Grants tab to see your monthly limits and how much you've used. Important: Free grants are tied to the free environment. If you delete your free environment, you lose the ability to use the free grants, and you can't get them back by creating a new environment. Availability Logic Apps Automation is in public preview in Australia East, East Asia, North Central US, Southeast Asia, Sweden Central, UK South, and West US. Preview pricing and availability may change before general availability. Get started If you already have an Azure subscription, your included grants are available to help you start building today. Create your first Automation project, start from a template or with the AI workflow assistant, and explore what you can build with Logic Apps Automation. Get started with Logic Apps Automation Quickstart: build your first workflow Read the full pricing details MS Learn documentation Watch the Logic Apps Automation video series Share feedback or request a feature, or just let us know what you build with Automation!Closing the AI Agent Governance Gap with Microsoft Foundry
Developers are shipping agents faster than security teams can catalog them. As organizations move beyond pilots and begin operating dozens or hundreds of agents, one question keeps coming up: how do we actually get visibility into our AI agents across our environment? In this article, we'll walk through how Azure services can help establish visibility, guardrails, and cost accountability across your AI estate. Governance for AI happens across four layers: Resources – who can create new AI resources Builders – who can develop and publish agents in a certain scope Behavior – how agent outputs are evaluated, monitored, and governed Dependencies – what models, tools, APIs, and MCP servers agents can interact with Most organizations already have governance controls for identities, networking, and compliance. The challenge isn't creating new controls. It's connecting existing controls into an operating model that works for AI agents. Below we walk through each area and go a bit deeper on how to close the gap. Setting up boundaries with Azure Policy First, let's start in the Azure portal with Azure Policy. Azure Policy lets you set guardrails on what can be deployed in your environment and flags or blocks anything that doesn't comply. For AI workloads, the built-in definitions range from limiting models that people in your organization can deploy to locking down the network through enabling private endpoints. Some policies you get started with: Foundry model deployments should only use approved models: Restricts deployments to models or publishers your organization has explicitly approved Foundry model deployments should meet eligibility requirements (preview): Applies rules based on model attributes like preview vs. GA status and distribution source Azure AI Services resources should have key access disabled: Makes Microsoft Entra ID the only entry point The full list of policies related to Azure AI Services are available here: List of built-in policy definitions - Azure Policy | Microsoft Learn Why this comes first: Policy checks resources before they are created, so it proactively keeps your environment aligned with your standards. Implementing role-based access control (RBAC) Once these boundaries are in place, the next step is RBAC. Setting RBAC up early ensures that people and identities building agents have the right scope for what they actually need to do. Foundry roles only apply when you authenticate using Microsoft Entra ID. If you're using key-based authentication instead, the key grants full access with without role restrictions. API keys are convenient for quick development usage but when moving towards production, Microsoft Entra ID is the preferred method. Roles can be assigned at three scopes: the Foundry resource, a Foundry project, or an individual agent itself. Below is an example of how different personas within organization can map to a certain scope for creating and building agents with Foundry. Here's how each role in the diagram compares, from least to most privileged: Role Privilege Level What it does in Microsoft Foundry Foundry Agent Consumer Least Interact with agent endpoints in a project. This is your least-privilege role for people who only need to use agents. Foundry User Low Grants reader access to the Foundry project, the Foundry resource, and data actions for your Foundry project. Least-privilege access role for developers building and testing agents. Foundry Project Manager Medium This role lets you perform management actions on Foundry projects, build and develop with projects, and conditionally assign the Foundry User role to other user principals. Foundry Account Owner Higher Grants full access to manage Foundry projects and resources, and lets you assign the Foundry User role to other user principals. Foundry Owner Highest Grants full access to manage Foundry projects and resources to build and develop with projects. This role can also assign the Foundry User, ACR, and monitoring roles to users in the environment. Source: Role-based access control for Microsoft Foundry - Microsoft Foundry | Microsoft Learn For the agent resources themselves, assign managed identities rather than API keys since it lowers the risk of having compromised credentials. Note if you're scripting RBAC permissions: these roles were recently renamed from Azure AI User, Azure AI Owner, Azure AI Account Owner, and Azure AI Project Manager. The role IDs and permissions didn't change, so use the role definition GUID in your code to avoid issues while the rename rolls out. Observability in Microsoft Foundry Governance requires more than access control. Organizations also need evidence of how agents are being used. Observability provides the audit trail needed to investigate incidents, understand usage patterns, and track costs. The Foundry Control Plane brings these observability and governance tools together in one place, alongside services like Azure Monitor, Microsoft Entra, Microsoft Purview, and Azure Policy. In the Foundry portal, tracing is a good starting point. Once you connect an Application Insights resource to your project, Foundry turns on tracing automatically so every run, including the ones you test in the playground, is logged. After it is completed, you can search by Response ID or Trace ID to see the conversation history, token usage, run steps, tool calls, and inputs and outputs between the user and the agent. For more granular queries, you can write KQL to dive into individual agent runs or use the prebuilt Grafana dashboards in Azure Monitor. With client-side tracing, you can also export traces to observability tools you may already use, such as Datadog or Jaeger. Note: Permissions required for viewing this telemetry requires the Log Analytics Reader role on the connected Application Insights resource, and Privileged Monitoring Data Reader on top of that if the underlying Log Analytics tables are protected. Alongside all of these monitoring features, every agent comes with content safety guardrails and evaluations let you test and optimize performance before and after you publish your agents. When agents get published to Microsoft Teams and Microsoft 365 Copilot, Microsoft 365 admins can approve usage requests. These requests can be further scoped to a limited group for pilot testing/department usage or the full organization. Adding an AI gateway Observability tells you what your agents are doing, but how do you actually control them? This is where Azure API Management comes in. Once you have more than one agent, model deployment, or multiple teams consuming them, you need a single enforcement point between the agents and the resources they call. Adding Azure API Management in front of Microsoft Foundry gives you: Rate limiting and load balancing across regions and model deployments Consistent authentication and quota policies for model and tool traffic Usage tracking per team or cost center so you can accurately charge back to different departments Governed access to your custom and remote MCP servers Note: When choosing MCP servers, start with trusted, enterprise supported sources (GitHub, Microsoft, internally developed servers, etc.) that have documented security controls, enterprise authentication, clear ownership, and least-privilege permissions. Treat community MCP servers as untrusted until they have undergone a formal security review and are verified by organizations. Adding an AI gateway completes the governance picture. Azure Policy governs what can be deployed. RBAC governs who can build and manage agents. Observability provides evidence of how agents behave in production. The AI gateway extends governance into runtime, controlling how agents interact with models, tools, and external systems. Combined, these layers help organizations move beyond simply building agents to operating them responsibly at scale. Extend governance across the wider estate A few directions to take this further: MCP registry in Azure API Center – As MCP usage grows, you can create an approved inventory of MCP servers and APIs that can be used across an organization. Microsoft Agent 365 – Microsoft's enterprise control plane for AI agents. It gives every agent its own Microsoft Entra Agent ID and published Foundry agents sync to its registry automatically. This gives your IT team one place to run access reviews, lifecycle policies, and owner attestation across every agent in the tenant, including shadow agents discovered outside Foundry. Copilot Studio – when you add an MCP tool, you can point it at the API Management URL instead of the direct remote endpoint to gain additional observability through the gateway. GitHub Copilot – you can apply the same AI gateway-fronted MCP registry, applied to the developer side. Microsoft Purview – data classification, DLP, audit, and AI interaction governance across the wider estate. Where to go next Looking for a quick start? Turn on the three Azure Policy definitions above in audit mode against a non-production subscription and see what gets flagged that is out of compliance. Ready to design the end-to-end pattern? Take a look at this Cloud Adoption Framework guidance on AI governance and governing Azure platform services for AI. Want to go deeper on agent observability? Start with these articles around Application Insights integrations with Foundry: Use Insights in Microsoft Foundry and Monitor AI Agents with Application Insights Governing AI agents doesn't require starting from scratch. The identity, policy, monitoring, and cost controls you already use for the rest of your Azure estate can extend to AI workloads. Start with one layer, connect the next, and build a governance foundation that grows with your AI adoption.
