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

Lemma

Founded 2024

Monitor production AI agents to detect silent failures and regressions

Pricing model

Demo

Rating

★ Mixed Reviews

Time to value

Moderate Setup (1-3 hours)

You can use Lemma to track and monitor how your AI agents perform in production. It audits traces against original system instructions to catch silent failures where agents return successful responses despite making errors. The system groups recurring issues together and delivers alerts directly to Slack with trace details. You can connect your coding agents via Model Context Protocol to fix prompts directly in your development workflow, then track online evaluations to confirm regressions do not happen.

What Lemma does

Audit agent execution traces against prompt instructionsGroup related agent errors into single incidentsSend failure alerts and trace snippets to Slack channelsInspect individual spans and token logs for root causesConnect incident context to coding agents via MCPTest updated prompts against previous failing tracesTrack live online evaluations to monitor prompt regressionsAudits production agent execution traces against original system promptsSurfaces silent failures that avoid traditional error trackingGroups repeating agent failure patterns into triageable issuesSends incident notifications and root-cause summaries to SlackProvides an MCP server to pull incident context into coding agentsRuns online evaluations after prompt updates to catch regressionsEncrypted data isolation with SOC 2 Type II compliance standards

Pricing breakdown

Pricing model: Book a demo

Tutorials & Demos

Frequently asked

SlackSlackGithubGithub

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Lemma, AI agent monitoring, agent observability, silent failure detection, prompt debugging, trace auditing, Model Context Protocol, Slack alerts, regression testing