Tessary cut agent reliability evaluation cost by 5x using layered trace classifiers
Builders struggle with costly and incomplete sampled evaluations for agent reliability; Tessary’s layered approach lowers cost and improves coverage by cheaply filtering traces before deep analysis, enabling scalable, continuous reliability monitoring.
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Tessary launches layered AI agent reliability platform
Tessary introduced an open-source platform that monitors every production agent trace with cheap L1 classifiers to flag potential errors and runs expensive L2 agents only on flagged traces for root cause analysis. This approach reduced evaluation cost by 5x at 1 million traces compared to sampled evaluations, improving coverage and lowering cost simultaneously.