Do you know when your AI
hallucinates?
deviates from instructions?
outputs irrelevant results?
generates unsafe outputs?

Discover the worst problems, prioritize, and rapidly optimize your AI applications.

AIMon helps startups and Fortune 200 companies overcome the challenges of deploying LLMs and RAG with deterministic precision.

Monitor any AI App. Anywhere.

AIMon feature supported Monitor your internally-built apps and your AI vendors too

AIMon can monitor your internal RAG, LLM, Agentic apps AND your AI vendors too.

AIMon feature supported Seamlessly observe production and development workflows

With AIMon's continuous monitoring, you don't need to restrict yourself to evaluating offline. You can get live insights that help you optimize your apps.

AIMon feature supported Deploy AIMon hosted or on-premise

AIMon can be deployed on-premise or hosted in the cloud to suit your company's trust policies.

AIMon vs. LLM-based Evaluations

Find out why Fortune 200 companies use us.

AIMon

Benchmark-leading, Consistent, Low-latency, and Pre-aligned Judges

  • Easily run on your company’s network, or hosted on AIMon.
  • No Evaluation Prompts Required!
  • Just select which metrics you desire and call a single API!
  • Real-Time Monitoring And Improvements!
  • Consistent Scores, Easy To Separate Good From Bad!
  • Aligned judges for higher task-accuracy!
  • Multiple metrics computed in parallel.
  • End-to-end visiblity into data quality, RAG, and LLM output.

LLM Judges

Most OSS and Properietary frameworks

  • Run on LLM Providers or you self-host multiple OSS models.
  • Need to write and tune Evaluation Prompts.
  • Write an Evaluation Prompt for each metric.
  • High Cost and Latency hinder real-time evaluations.
  • Suffers from scoring inconsistency.
  • Subjectivity.
  • Parallel calls result in resource contention and rate limits.
  • Limited visibility into a single aspect of your app.
Judging-as-a-service
Benchmark-leading. Lightning fast. Models that run in parallel to provide unprecedented insights into the behaviour of your AI.

Output / Hallucination

Identify phrase-level, contextual, and general-knowledge hallucination scores better than GPT-4o in a few hundred milliseconds.

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Output / Instruction Adherence

Check if your LLMs deviate from your instructions and why. 87%+ accuracy and <500ms latency.

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RAG / Context Issues

Identify context quality issues like conflicting information to troubleshoot and fix root causes of LLM hallucinations.

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RAG / Context Relevance and Reranking

Determine the query-context relevance scores for your retrievals with a model that ranks in the top 5 on the MTEB leaderboard. Use the feedback and rerank your retrievals with our reranker.

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Output / Completeness and Conciseness

Check if your LLMs captured all the important information expected or when they talked too much.

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Output / Toxicity and Bias

Detect hate speech, obscenities, discriminatory language, bias, and more.

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Optimize LLMs, RAG, Agentic, and even Vendor AI Apps. Explainability, insights, reports, and improvement datasets.
AIMon value prop

Getting started with AIMon is free and easy

1

Sign up

Explore our GitHub and NPM pages for ready-made example apps. Starting to use AIMon takes 15 minutes.

2

Check out the Docs

Review examples and recipes that help you improve your apps.

3

Integrate AIMon

Unlock instant or offline insights into your LLM apps with our powerful SDKs and API.

4

Optimize

Find top problematic LLM Apps, identify quality issues and gain critical insights to optimize effectively.

Resources
  • How AIMon's Benchmark-leading "Checker Models" outshine LLMs for evaluation and monitoring.

  • How to improve RAG Relevance by over 100% and overall output quality by 30% in your RAG and LLM Apps with AIMon.

  • How to build Accuracy Flywheels for your LLM/RAG Apps. And a demo of how to detect Hallucinations with AIMon.

Reach out to us

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