About
Built from production inference experience.
InferNext came out of running an LLM inference platform in production. The same pattern kept showing up: a team picks an open-weight model on published benchmarks, builds around it, ships it, and only then finds out how it behaves on their own data and their own traffic.
By then the answer is expensive. The integration exists, the model is load-bearing, and changing it means redoing the work. What was missing was a step before that one: somewhere to prove the model first, and a path that carries the proven artifact into production unchanged.
Why InferNext exists
The step that was missing.
Evaluation and benchmarking are not new ideas. What is missing is one place to do both against a real endpoint, with your own data and your own traffic shape, while the decision is still reversible.
And then the part that is easy to skip: carrying the exact artifact you validated through to production, unchanged. A result you cannot ship is only a rehearsal.
That is the whole product. Evaluate, benchmark, promote, with the same artifact from end to end.
Founder
Nurali Virani — Founder
More than ten years building large-scale production systems, most recently building and operating an LLM inference platform serving open-weight models. Contributor to vLLM. InferNext is the step that platform kept needing.
Status
Early, and working with design partners.
InferNext is pre-launch. If you are making an open-weight model decision now, or you have run into this gap yourself, a conversation is useful to us and probably to you.