/services
Production AI is 10% models, 90% data engineering. I handle the hard 90%.
Infrastructure Bootstrap
For teams who want AI but fear the data mess.
A 2-week deep dive to map your data, define access patterns, and establish the governance needed for safe RAG/Agent deployment.
- Compliance/Risk Register
- RAG Feasibility Scorecard
- Access Control Architecture
Fixed Scope (2 Weeks)
Book Fit CheckRAG/Agent Production Path
From "Cool Demo" to "Reliable System".
We ship a working agent integrated into real workflows (SQL/NoSQL/Graph), hardened with evaluation loops and observability.
- Working End-to-End Pipeline
- Eval Harness (Precision/Recall)
- Cost & Latency Controls
Project Based
Discuss ArchitectureOps & Governance
Prevent drift. Ensure safety.
Ongoing engineering support for data contracts, prompt drift, retrieval quality, and schema evolution.
- Weekly Tuning & Evals
- Data Pipeline Maintenance
- Incident Response SLA
Monthly Retainer
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