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MLOps & evals

Models in production are software in production. We bring the SRE, the eval rigor, and the cost discipline to make them stay in production.

MLOps & evals
What we actually do

The work, on one page.

Eval infrastructure

Golden datasets, regression suites, and live drift checks — wired into the deployment pipeline, not a quarterly review.

Inference platform

Model gateway, routing, caching, and FinOps — so the cost curve doesn't eat the value curve.

Lifecycle ops

Retrain triggers, rollback plans, and the runbooks a Tier-1 ops team can actually follow.

Receipts, not narratives

Recent work.

Insurance

Models that age gracefully.

Stood up the eval and retrain pipeline that turned a one-off pricing model into a durable platform asset.

Common questions

The honest version.

Do you replace our MLOps team?+

No. We build the platform with them, then leave the platform running and the team owning it.

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