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Datadog for Agent Reliability
Sentrial is the monitoring platform for AI products in production. When your AI product/agent loops indefinitely, hallucinates, or frustrates users, Sentrial detects it in real-time, diagnoses the root cause, and recommends specific fixes. We provide the monitoring, evaluation, and debugging infrastructure that traditional tools weren't built for, so teams iterate based on production reality, not just offline evals.
Sentrial positions itself as observability for AI agents, aiming to detect regressions and drift across agent sessions, tool calls, and LLM interactions. It markets itself as catching silent regressions before users notice, focusing on AI agent reliability.
Sentrial provides observability for AI agents by monitoring and detecting drift and regressions across all agent interactions, including sessions, tool calls, and LLM interactions, enabling proactive identification of issues before end users are affected.
Who it’s for: Teams building AI agents or decision agents that interact with tools and LLMs, requiring reliability and monitoring across agent behavior and interactions.
Neel is the founder of Sentrial - production monitoring for AI products. He studied Computer Science at UC Berkeley and worked on agentic optimization at Sense. He saw firsthand that traditional evaluation frameworks break down once agents hit production. That insight led to the creation of Sentrial, a platform built to monitor, evaluate, and improve agent performance in real-world, production environments. contact: neel@sentrial.com
Sentrial helps engineering teams detect, diagnose, and fix AI agent issues in production.
Sentrial provides production monitoring for AI agents, offering real-time visibility into agent behavior and automatically detects failure patterns such as loops, hallucinations, tool misuse, and user frustration. It diagnoses root causes from conversation patterns, model outputs, and tool interactions, and recommends fixes for engineering teams.
Formerly “Realm” · why startups rename →
Monitoring and learning layer for long-running agents
Reliability platform for AI agents
