AI
Cloud-agnostic by design. We ship retrieval pipelines, fine-tuned models, and agentic systems that run in production — not slide decks.
Most AI projects stall in proof-of-concept. Models that look brilliant in a demo break the moment real users hit them with edge cases, latency requirements, or compliance constraints. The gap between "it works in a notebook" and "it works for paying customers" is where real engineering lives.
By the numbers
50+
Production AI systems deployed across cloud providers
<200ms
Median retrieval latency at production scale
30%
Average reduction in inference cost via prompt + model optimization
Retrieval-augmented systems that work in production. Hybrid search, re-ranking, citation-grounded answers, real-time index updates — built around your actual data, not a tutorial pipeline that breaks at scale.
Fine-tuning when it earns its keep. We help you decide between prompting, retrieval, and fine-tuning based on cost, latency, and quality data — and execute the one that fits. No fine-tuning theater.
Agentic systems with real tool use. Multi-step agents that call your APIs, query your databases, and take actions — with auditing, rollback, and human-in-the-loop where it matters.
Eval harnesses you can trust. Automated quality, safety, and regression evals that catch model drift before your users do. Set up once, runs on every deploy.
What you get
Multi-cloud, multi-model
We've shipped production AI on every major foundation model and cloud. We pick the right combination for your latency, cost, and quality requirements — not the one we're locked into.
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