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AI Integration & AI-Native Products

LLM features engineered for production — not demos.

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The gap between a working demo and a reliable AI product is enormous — and it's almost entirely an engineering problem. Evals, observability, cost control, prompt versioning, and graceful failure are what separate a feature you can operate from a feature you can only hope works.

How we approach it

LLMs are non-deterministic systems. We treat them as such: with measurement, version control, regression gates, and clear failure modes. The model is one component in a system designed and operated by senior engineers.

What you get

A shipped AI feature with documented quality targets, predictable cost, an eval suite that catches regressions before users do, and a path to iterate without breaking what already works.

Capabilities

  • LLM feature design with measurable quality targets
  • Retrieval-augmented generation (RAG) on pgvector and managed stores
  • Embedding pipelines, chunking strategies, and freshness controls
  • Agentic and tool-use workflows with bounded autonomy
  • Evaluation harnesses wired into CI
  • Prompt, model, and dataset versioning with rollback
  • Per-request cost and latency observability

Deliverables

  • Production AI feature with documented quality targets
  • Eval suite with regression tracking on every commit
  • Versioned prompts, models, and datasets
  • Cost and latency dashboards with alerting
  • Runbook for drift, incidents, and model swaps

Typical stack

OpenAIAnthropicpgvectorLangChainVercel AI SDK

Questions

Common questions

Funded startups, SMEs, and enterprise innovation teams. We've shipped MVPs for pre-seed founders and migrated platforms for public companies.

Fixed-scope sprints for MVPs (4–12 weeks), monthly retainers for ongoing product teams, and short architecture engagements (1–3 weeks) for audits.

Shared Slack or Linear, weekly written updates, a public roadmap, and a live demo every Friday. No status meetings for the sake of meetings.

Yes. All IP is yours from day one. We commit directly to your repository under your license.

Work with us

Ready to talk specifics?

Start with a short discovery call about your ai integration & ai-native products project, or send full details. A senior engineer replies within one business day.

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