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AI Integration

AI integration is not a chat box dropped into a page—it is retrieval, tool execution, evaluation, and safety layered onto your existing product. We design systems where models are grounded, actions are constrained, and failures are observable.

RAG / RetrievalTool CallingEval & ObservabilityAI AutomationAPI IntegrationSafety Layering

Deliverables

  • —RAG system design: ingestion, chunking, embedding strategy, retrieval tuning
  • —Tool-calling and agent-adjacent workflows with policy boundaries
  • —Evaluation harnesses, logging, and production monitoring hooks
  • —API surfaces and UI patterns for human-in-the-loop review

How we work

  1. 01Audit data sources, latency budgets, and risk surfaces
  2. 02Prototype retrieval + tool paths behind feature flags
  3. 03Harden with eval loops, red-team scenarios, and rollout plans

Ideal for

  • Teams shipping copilots on internal or customer data
  • Products that need automation without losing auditability

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