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Enterprise Layer Intelligence
Categories/AI Orchestration & MLOps/Bento
Bento

Bento

Founded by Jesse Hanley in 2024

Monitor, evaluate, and fix production AI agents using OpenTelemetry traces

Pricing model

Demo

Rating

★ People love it

Time to value

Moderate Setup (1-3 hours)

You can use Bento to observe, test, and improve AI agents running in production. It captures OpenTelemetry-native traces across agent frameworks to detect behavioral drift, broken tool calls, and prompt regressions. You can define failure modes in plain English, and Bento flags them in real time while searching historical data to check when issues began. It helps teams test prompt and model updates against historical production runs, maintain version control, and auto-generate new skills or subagent fixes from production failures.

What Bento does

Inspect OpenTelemetry execution traces for multi-step agentsSet up plain-English alerts for agent failure patternsRun regression evaluations in CI pipelines using production logsCompare prompt and model diffs across releasesPinpoint behavioral drift between model versionsRoll back failing prompt updates to previous working statesOpenTelemetry-native trace collection across any AI agent frameworkPlain-English alert configuration that filters out false alarmsAutomated detection of behavioral drift across agent runsOffline, CI, and canary evaluations scored against real production historyAuto-authored skills, subagents, and tools created from production failuresVersioned, diffable, and reversible prompt, model, and skill trackingBackfilling historical traces to determine when regressions first started

Pricing breakdown

Pricing model: Book a demo

Tutorials & Demos

Frequently asked

OpenTelemetry

Used by

Thomas Sanlis

Thomas Sanlis

Founder / CEO @ writizzy.com

In their stack
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Bento, AI agents, agent observability, OpenTelemetry, evals, agent evaluations, regression testing, drift detection, tracing, MLOps, LLM monitoring