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Sentrial

Observability for AI agents: catch drift and silent regressions across sessions and tool calls.

Sentrial monitors AI agents in production for loops, hallucinations, tool misuse and silent regressions across every session, tool call and model interaction ("Catch agent drift before your users do"). It launched on Hacker News in March 2026. Y Combinator W26.

Featured

The de-facto standard toolkit for building LLM applications and agents.

LangChain makes the LangChain framework and LangGraph, the low-level orchestration standard for stateful, controllable agents, plus the LangSmith platform for tracing, evaluating and monitoring them in production.

~$75M raised

Enterprise-grade evals, data and AI gateway.

Braintrust turns prompts and agent traces into testable datasets and CI, plus an inference gateway — helping teams measure whether harness changes actually improve agent quality.

Observability and evaluation for AI — makers of OSS Phoenix.

Arize traces and evaluates LLM and agent systems in production; their open-source Phoenix tracer is a common instrumentation choice for agent harnesses that need to be debuggable.

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Similar entries · 3

Sources

  1. Sentrial homepage