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Ajah adds observability to LangChain and LlamaIndex agents

Ajah has released new integrations for LangChain and LlamaIndex, providing developers with tools to monitor agent performance and costs. These integrations offer features such as cost attribution per step, hallucination risk detection, claim density analysis, and narrative drift monitoring. The system aims to give users full observability into their LLM agents, with a self-hosted dashboard displaying session traces, warnings, and overall cost breakdowns. AI

IMPACT Enables developers to better monitor and debug their LLM agents, potentially improving reliability and cost-efficiency.

RANK_REASON This is a product launch for a tool that integrates with existing LLM frameworks.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · Vignesh Reddy ·

    How to add full observability to your LangChain and LlamaIndex agents in under 10 minutes

    <p>If you're running LangChain or LlamaIndex <br /> agents in production, you're missing <br /> critical signals.</p> <p>You know what your agent said.<br /> You don't know what it cost per step.<br /> You don't know when it hallucinated.<br /> You don't know when it reversed a p…