M
Michael Marolda
Guest
The October release adds a native Microsoft Teams application to Progress Agentic RAG, giving any AI experience your organization has already built a direct path into the tool your employees use every day. It's available through the Microsoft Teams store, runs on the same knowledge layer and governance your deployment already has in place, and requires no rebuild to turn on.
You've likely already seen this pattern play out. A team builds a genuinely capable AI assistant — strong retrieval, accurate answers, solid governance — and deploys it to a portal or a standalone application. Usage never takes off. Employees already move between roughly nine applications a day, and asking them to add a tenth just to consult an AI assistant is a real cost, not a minor inconvenience. The assistant that gets used is the one that's already where people are working.
That puts you in an uncomfortable position. You approved the AI investment, and the number you're evaluated on isn't retrieval accuracy: it's usage. A technically excellent deployment that nobody opens reads to the board and the CFO as a failed bet, no matter how sound the underlying architecture was. And every additional delivery surface your organization wants (Teams today, something else tomorrow) has historically meant scoping a new front-end project, which slows the roadmap and adds cost that has nothing to do with improving the AI itself.
Progress Agentic RAG now deploys directly inside Microsoft Teams as a native application, distributed through the Microsoft store. Nothing about the underlying deployment changes — the same indexed content, the same access controls, the same source-cited and quality-scored answers your team already trusts. What changes is that employees can now ask questions inside the application they already have open, instead of being asked to visit somewhere else first.
In practice, this opens up a few different ways to put the same deployment to work:
A capability every future deployment inherits. For organizations running more than one internal AI use case, each one built on Progress Agentic RAG inherits the same Teams delivery automatically — this isn't a one-time integration project, it's a capability every future deployment gets by default.
The most immediate benefit is that the adoption objection you've been fielding on every AI proposal now has a real answer, and it costs nothing further to implement. Delivery surface becomes a configuration choice instead of a new project, which means the engineering investment your team already made finally reaches the people it was built for without asking for another dollar of budget to get it there.
It also changes the shape of your next roadmap conversation. Instead of defending a caveat about usage, you're presenting a distribution story backed by a number people already understand: hundreds of millions of Teams users across a huge base of organizations already standardized on Microsoft. And because this is inherited automatically by any future AI experience built on the same knowledge layer, you're not solving distribution once you're solving it permanently, for whatever your team decides to build next.
For a deployment you've already justified to the board once, that's the difference between defending it again next quarter and pointing at a track record instead.
Learn more about Microsoft Teams in Progress Agentic RAG today.
Continue reading...
A good deployment that nobody uses
You've likely already seen this pattern play out. A team builds a genuinely capable AI assistant — strong retrieval, accurate answers, solid governance — and deploys it to a portal or a standalone application. Usage never takes off. Employees already move between roughly nine applications a day, and asking them to add a tenth just to consult an AI assistant is a real cost, not a minor inconvenience. The assistant that gets used is the one that's already where people are working.
That puts you in an uncomfortable position. You approved the AI investment, and the number you're evaluated on isn't retrieval accuracy: it's usage. A technically excellent deployment that nobody opens reads to the board and the CFO as a failed bet, no matter how sound the underlying architecture was. And every additional delivery surface your organization wants (Teams today, something else tomorrow) has historically meant scoping a new front-end project, which slows the roadmap and adds cost that has nothing to do with improving the AI itself.
The assistant moves to where the work already happens
Progress Agentic RAG now deploys directly inside Microsoft Teams as a native application, distributed through the Microsoft store. Nothing about the underlying deployment changes — the same indexed content, the same access controls, the same source-cited and quality-scored answers your team already trusts. What changes is that employees can now ask questions inside the application they already have open, instead of being asked to visit somewhere else first.
In practice, this opens up a few different ways to put the same deployment to work:
- Internal knowledge assistant. Employees query Teams directly for policy questions, product documentation, or anything else your organization has indexed — no separate login, no new habit to build.
- Frontline and field reach. Because Teams is the standard collaboration surface across a huge share of enterprises, this also reaches frontline and field employees, or workers on shared devices, who were realistically never going to open a browser-based tool during a shift extending a deployment you've already paid for to people it couldn't reach before.
- Sales enablement and competitive intelligence. Reps can ask Teams for the latest battlecard, pricing guidance, or how to position against a specific competitor without digging through a wiki or pinging a colleague surfacing the same governed, source-cited content in the moment a deal actually needs it.
A capability every future deployment inherits. For organizations running more than one internal AI use case, each one built on Progress Agentic RAG inherits the same Teams delivery automatically — this isn't a one-time integration project, it's a capability every future deployment gets by default.
What this means for you
The most immediate benefit is that the adoption objection you've been fielding on every AI proposal now has a real answer, and it costs nothing further to implement. Delivery surface becomes a configuration choice instead of a new project, which means the engineering investment your team already made finally reaches the people it was built for without asking for another dollar of budget to get it there.
It also changes the shape of your next roadmap conversation. Instead of defending a caveat about usage, you're presenting a distribution story backed by a number people already understand: hundreds of millions of Teams users across a huge base of organizations already standardized on Microsoft. And because this is inherited automatically by any future AI experience built on the same knowledge layer, you're not solving distribution once you're solving it permanently, for whatever your team decides to build next.
For a deployment you've already justified to the board once, that's the difference between defending it again next quarter and pointing at a track record instead.
Learn more about Microsoft Teams in Progress Agentic RAG today.
Continue reading...