For Series A+ companies, ops teams, AI-curious founders

AI integration services that survive production.

GPT, Claude, Whisper, custom RAG, agents, voice. Wired into your existing app with cost guardrails and latency budgets. Not a demo — a deployed system.

Get a quotefrom $8,000 · USD

What's included

Production-grade AI integration services that ships, not theater.

  • Provider-agnostic LLM client (GPT-4, Claude, Gemini)
  • Custom RAG pipelines (Postgres pgvector, FAISS, Qdrant)
  • Agent workflows with tool use + structured output
  • Streaming responses (Server-Sent Events / WebSockets)
  • Cost guardrails, retry logic, fallback chains
  • Evals harness so quality survives prompt drift

What you walk away with

Deliverables you keep — code, infrastructure, and the runbook.

  • Integrated AI feature deployed to production
  • Eval suite + monitoring dashboard
  • Cost projection and per-user economics
  • Documentation for your team to extend it

Frequently asked

Which AI providers do you work with?+

OpenAI (GPT-4, GPT-4o, o1), Anthropic (Claude Sonnet, Opus, Haiku), Google (Gemini), and on-device (Whisper, KoboldCpp, CLIP, FAISS). Provider-agnostic clients let you swap models without rewriting features.

How do you prevent runaway AI costs?+

Per-user rate limits, request caching, prompt caching for repeated context, model-tier fallback (Sonnet for hard tasks, Haiku for cheap ones), and live cost dashboards. I share unit economics before launch so you know what each user costs.

Can you build a RAG system over my existing data?+

Yes — ingestion pipeline, chunking strategy tuned to your content, embeddings, hybrid search (vector + BM25), reranking, and evaluation. Postgres pgvector for most cases, Qdrant or FAISS for larger corpora.

Do you build AI agents that take actions?+

Yes — tool-use agents with structured output, guardrails, and approval gates for risky actions. I prefer narrow, observable agents over open-ended ones.

What about AI evaluation and quality drift?+

Every integration ships with an eval harness — golden examples, regression tests, and a dashboard. When you swap models or change prompts, you see quality impact before deploying.

Ready to scope your AI integration services?

Email me what you're building. I'll respond with a quote, scope questions, and a clear next step.