Production Monitoring for AI Agents
Hi all! Neel and Anay here - we’re building Sentrial, production monitoring for AI agent behavior.
TL;DR: Sentrial semantically detects when agents loop, hallucinate, misuse tools, or frustrate users in production, then helps engineering teams diagnose the root cause and fix it fast.
The problem
AI agents are becoming core infrastructure - handling customer support, automating workflows, and making decisions on behalf of users. But when something goes wrong, teams are flying blind. Traditional monitoring catches errors and latency, not failures like hallucinations or user frustration. No alert fires when an agent goes off the rails, and agents that were meant to scale operations end up requiring constant oversight.
What Sentrial does
Sentrial gives engineering teams real-time visibility into how their agents actually behave in production. We automatically detect failure patterns: loops, hallucinations, tool misuse, and user frustrations the moment they happen. When issues surface, Sentrial diagnoses the root cause by analyzing conversation patterns, model outputs, and tool interactions, then recommends specific fixes.
Ask
If your internal or customer-facing agents are looping, hallucinating, or frustrating users in production and it’s hard to diagnose, we’d love to talk. Email neel@sentrial.com or book a call here to learn more!
Team
Neel: CS @ UC Berkeley, worked on Agentic Optimization at Sense.
Anay: CS @ UC Berkeley, deployed DevOps agents at Accenture.
