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Moda

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The monitoring layer your AI agents need.

Winter 2026Founded 20252 peopleSan Francisco, CA, USA
AI insightcan contain mistakes
Agent Reliability & MonitoringSaaSAI teams, agent developers, companies deploying agentsMedium competition
Moat
Proprietary agent hallucination and failure pattern detection; user frustration signals; retention/churn metrics.
Key risk
Cloud providers (AWS, GCP) may add agent monitoring; commoditization risk; customer concentration in early-stage agents.
Why now
Agent deployments failing in production; need for agent-specific observability urgent; user trust and retention critical.
Competitors
Datadog, Sentry, New Relic, Vercel Analytics, Anthropic Console

About

Moda is the reliability & monitoring layer for agents. It surfaces patterns across agent hallucinations, laziness, forgetfulness, and tool call failures. While also providing analytics on user frustration, net promoter score, retention, and churn rates. In the next 10 years, with more AI agents spawning and trying to get PMF, developing an agent that actually works for users is critical. Everyone has access to the same models, thus the ones that win on a product level will be the ones who learn fastest from real usage. Moda is that learning layer.

Founders ยท 2

Pranav Bedi
Pranav BediFounder

Building Moda

Mohammed Al-Rasheed
Mohammed Al-RasheedFounder

Building Moda

Launch

Launched on Y Combinator ยท Mar 2026
View launch post โ†—

See What Your Logs Can't. Real Monitoring and Reliability for AI Agents.

Moda provides monitoring and reliability for AI agents, converting conversations and tool traces into actionable signals. It offers trace-first drilldowns, conversation segmentation, failure detection, quality and safety signals, and regression tracking to identify and debug issues in AI agent runs in production.

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