We already have infra. Can you improve it?
Yes. Most of our infra work is optimizing existing systems: cost, latency, evals, observability. We do not rip and replace unless it is the only option.
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AI Infrastructure & Scaling
LLM cost optimization, inference caching, eval pipelines, vector DB tuning, observability. The unsexy work that makes the difference between a demo and a production feature.
What you get
- LLM cost cut without sacrificing quality, measured per request
- Vector DB and retrieval tuned for latency and recall at scale
- Eval pipelines and observability so regressions get caught before users do
Technology stack
VercelAWSpgvectorRedisObservability
FAQ
Do you support post-launch operations?
Yes. Monthly retainer for ongoing engineering, on-call for production AI systems, and regular cost and eval reviews.