Overmind fine-tunes Qwen3.5 9B on production traces, cuts phantom contract clauses 20-30x
rohanpaul_ai · x · 2026-10-07
Overmind unifies observability and training: it builds a context graph from your code and agent traces, curates training and eval datasets from them, then fine-tunes a small open model scored against your current model on evals built from those same real tasks.
- Published comparison: Qwen3.5 9B tuned via Overmind vs GPT5.6 Luna on contract reading — 20-30x fewer phantom clauses (citing non-existent clauses) and 7x better accuracy at quoting clauses word for word.
- Key idea: the traces showing where your agent fails become the training dataset, and evals come from real tasks rather than public benchmarks.
- Output is a smaller open model with weights you own, hosted on Overmind or self-hosted.
(Numbers are company-reported, not independently verified.)
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