A custom-model platform that captures agent interactions, turns traces into training data, fine-tunes models, evaluates them, and serves the trained models.
Belvedir collects AI-agent calls, tool use, and replies through an SDK, then organizes traces into task groups and datasets for custom-model training. Its product workflow includes fine-tuning open models, evaluating training runs against benchmarks, and serving trained models through cloud inference or exporting weights for self-hosting. The site also describes keeping traces, datasets, and trained models isolated to a customer workspace. The company’s announcement describes the product as a private AI platform for training and hosting custom models and memory systems.
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