(00:00:00) The Limitations of AI Without Data
(00:00:30) The Data Gateway: A Secure Bridge
(00:00:49) The Power of Structured Data
(00:03:14) The Data Gateway Explained
(00:04:12) Secure and Scalable Implementation
(00:07:16) Teaching Copilot to Read Your Data
(00:11:33) Giving Copilot Hands: Controlled Write Backs
(00:16:36) Designing the Hybrid Brain
(00:20:08) The Secret to Hybrid AI Success
🔍 Key Topics Covered 1) Why Copilots Fail Without Context
- LLMs without data grounding = fluent hallucinations and confident nonsense.
- The real memory lives in SQL Server—orders, invoices, inventory—behind the firewall.
- Hybrid parity goal: cloud intelligence with on-prem control, zero data exposure.
2) The Power Platform Data Gateway — Spine of Hybrid AI
- Not “middleware”—your encrypted, outbound-only tunnel (no inbound firewall punches).
- Gateway clusters for high availability; one gateway serves Power BI, Power Apps, Power Automate, and Copilot Studio.
- No replication: queries only, end-to-end TLS, AAD/SQL/Windows auth, and auditable telemetry.
3) Teaching Copilot to Read SQL (Knowledge Sources)
- Add Azure SQL via Gateway in Copilot Studio; choose the right auth (SQL, Windows, or AAD-brokered).
- Expose clean views (well-named columns, read-optimized joins) for clarity and performance.
- Live answers: conversational context drives real-time T-SQL through the gateway—no CSV exports.
4) Giving Copilot Hands — Actions & Write-Backs
- Define SQL Actions (insert/update/execute stored procs) with strict parameter prompts.
- Separate read vs write connections/privileges for least privilege; confirmations for critical ops.
- Every write is encrypted, logged, and governed—from chat intent to committed row.
5) Designing the Hybrid Brain — Architecture & Scale
- Four-part model: SQL (memory) → Gateway (spine) → Copilot/Power Platform (brain) → Teams/Web (face).
- Scale with gateway clusters, indexes, read-optimized views, and nightly metadata refresh.
- Send logs to Log Analytics/Sentinel; prove compliance with user/time/action traces.
🧠Key Takeaways
- Copilot without SQL context = eloquent guesswork. Ground it via the Data Gateway.
- The gateway is outbound-only, encrypted, auditable—no database exposure.
- Use Knowledge Sources for live reads and SQL Actions for safe, governed writes.
- Design for least privilege, versioned views, and telemetry from day one.
- Hybrid done right = real-time answers + compliant operations.
âś… Implementation Checklist (Practical)
- Install & register On-Premises Data Gateway; create a cluster (2+ nodes).
- Create environment connections: separate read (SELECT) and write (INSERT/UPDATE) creds.
- In Copilot Studio: Add Knowledge → Azure SQL via gateway → select read-optimized views.
- Verify live queries (small, filtered result sets; correct data types).
- Define SQL Actions with clear parameter labels & confirmations.
- Enable telemetry export to Log Analytics/Sentinel; document runbooks.
- Index & maintain views; schedule metadata refresh.
- Pen test: cert chain, outbound rules, least privilege review.
- Pilot with a narrow use case (e.g., “invoice lookup + create customer”).
- Roll out with RBAC, DLP policies, and change control.
🎧 Listen & Subscribe If this saved you from another late-night CSV shuffle, follow the show and turn on notifications. Next up: extending the same architecture to legacy APIs and flat-file systems—because proper wiring beats magic every time.
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If this clashes with how you’ve seen it play out, I’m always curious.
I use LinkedIn for the back-and-forth.
