Custom copilot Teams Integration in Government applications

on YouTube ↗36m

" summary

Two government customers build and deploy Teams-based copilots using Azure OpenAI (GPT‑4 and GPT‑3.5), Azure AI Search/vector retrieval, semantic kernels and the Teams AI library; one prototype stands up in days using GitHub samples, app service, Key Vault, blob transcript logging and a Teams manifest. One deployment indexes about 5 million decisions for courts with narrow citations and Copilot plugin links; another reports productivity gains of about 2–5 hours per week per user and production-ready secure GCC High configuration.

AI-written summary · about

" chapters (30)

1. 0:00Custom Copilot Teams intro
2. 1:18L3Harris AI assistant
3. 3:44Azure OpenAI and Teams choice
4. 4:47Security and productivity priorities
5. 5:49Development journey and GitHub
6. 6:54Bleeding edge AI adjustments
7. 7:55Architecture deep dive and repos
8. 11:10Government cloud security setup
9. 12:39Core bot and Semantic Kernel
10. 14:53MVP features and error handling
11. 16:41Teams manifest and adoption
12. 18:48Live demo: L3Harris Copilot
13. 19:31Accelerating MVP with GitHub
14. 20:13Early AI adoption advice
15. 20:55Measuring AI ROI
16. 21:17Future plans: internal data
17. 22:21Studio 365 and Court of Justice intro
18. 24:07Jurisprudence GPT overview
19. 25:51Live demo: Jurisprudence GPT
20. 27:21Azure OpenAI impact on dev
21. 28:04Court of Justice reaction
22. 28:46User feedback and search
23. 29:07Productivity gains expected
24. 30:11Learning curve and team
25. 30:57Tech and architecture overview
26. 31:42Development tools and process
27. 32:03Copilot for M365 integration
28. 33:08Future plans for Jurisprudence GPT
29. 34:11Copilot dev advice
30. 34:53Closing remarks

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