▸ AI Integration Sprint
AI that ships into your product, not a demo.
Claude tool use, MCP servers, RAG on pgvector, and an eval harness your team can run. Pragmatic AI wired into the product you already have.
Who this is for
- Product teams that want Claude or MCP capabilities inside an existing SaaS.
- Engineering leads who need RAG that survives production traffic and cost limits.
- Founders past the prototype who need evals, auth, and audit trails before launch.
What you get
- Claude API integration with tool use shaped to your domain
- MCP server build or hardening (auth, audit logging, structured errors)
- RAG on pgvector with hybrid search when keyword recall still matters
- Eval harness and cost guardrails so regressions and spend stay visible
- Handoff docs so your team can extend tools and prompts safely
How it works.
▸ Same process across every package
- 01
Discovery call
Free 15-minute call. We scope the problem, I tell you honestly if I'm the right fit and what it'll take.
- 02
Fixed proposal
You get a written scope, milestones, and a flat price or weekly rate. No open-ended hourly surprises.
- 03
Build in the open
Short async updates, a shared board, demos every few days. You see progress, not a black box.
- 04
Ship + handoff
Deployed, documented, tested. I hand off clean code your team can own — or stay on retainer.
Related writing and work
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▸ Post
MCP first is the new mobile first
Why tools, skills, and permissions come before another chat UI.
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▸ Post
MCP auth and audit logging
Tenant-safe MCP in Laravel: who called what, and how you prove it.
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▸ Post
Why RAG fails in production
Common failure modes and the fixes that actually move quality.
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▸ Page
MCP server for internal SaaS
A production MCP surface wired into a real multi-tenant product.
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▸ Page
Production RAG on pgvector
Hybrid search pipeline that held up past the demo stage.
Questions, answered.
How long is the AI integration sprint?
Usually 2-4 weeks for a focused feature: one MCP surface, a RAG path, or Claude tool use with evals. Larger agent platforms get a longer proposal after discovery.
Do you only work with Laravel?
Laravel is my deepest stack for multi-tenant SaaS and MCP, but the patterns transfer. We meet your product where it is and keep the integration boring and testable.
Will this burn my API budget?
Cost guardrails are part of the sprint: caching, rate limits, token budgets, and eval gates so you see spend and quality before users do.
What about model lock-in?
I default to Claude where tool use is strong, and keep provider boundaries thin so you can swap or dual-run later. No opaque SDK spaghetti.
Ready to add real AI?
Free discovery call. We pick one high-value surface, not a kitchen-sink agent rewrite.