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Artificial Intelligence

Models that survive contact with production.

We take AI from notebook to system: retrieval, evaluation, guardrails, cost control, and the monitoring that catches drift before customers do.

Challenges

What we see repeatedly

  • Demos that impress but never ship
  • No objective way to tell if a change made quality worse
  • Inference costs scaling faster than revenue
Approach

How we address it

  • Evaluation harnesses gating every prompt and model change
  • Retrieval architectures grounded in your own corpus
  • Routing and caching strategies tuned to cost per resolved task

Working in artificial intelligence?

We’ll tell you in the first conversation whether we think we’re the right fit — including when we think we’re not.

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