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Open-weight GenAI at Scale

Running open-weight language models inside the enterprise boundary, sized, evaluated and governed for production.

Sector
Enterprise AI
Year
2025
Where it runs
Inside your boundary
IL-18 · spec sheet

in

  • Open-weight models
  • The client's own infrastructure
  • One evaluation set per use case

engine

  • Served behind one gateway
  • Guardrails and logging on every call
  • Sized for the work, not the demo

out

  • Models that never leave the boundary
  • Quality measured against the real job
  • Costs known in advance

The problem

Many enterprises cannot send their data to a hosted model, but running models themselves raises new questions about sizing, cost, quality and control.

What we built

A blueprint for running open-weight language models inside the enterprise boundary: choosing models for each task, serving them efficiently, evaluating them against the work they will do, and governing what they can see and do.

How it works

Models are served on the client’s own infrastructure behind one gateway. Each use case gets its own evaluation set, and guardrails and logging apply to every call.