Control yourAI.AI.

Traces and training data stay in your account and never train anyone else's models. Inference can run in your own VPC or on dedicated single-tenant hardware.

We use your third-party data and production traces to build training data and environments. From there, we train model weights using RL techniques, and memory layers using optimizers.

It's a bit of a buzzword. Our interpretation is concrete: ultra-frequent fine-tuning and memory updates, made in response to the tasks your agent or model actually experiences in production.

No. Training and inference run on managed infrastructure by default, and you can deploy finished models into your own VPC or on dedicated hardware whenever you're ready.

A fine-tuning API gives you one static checkpoint. Belvedir gives you the whole loop: trace collection, training data curation, benchmarks, and repeated improvement, with weights and memory you own at the end.

No. Belvedir sits alongside whatever you run today. Start by collecting traces from your existing agents, then swap in your own models gradually as they beat the incumbents on your benchmarks.