Use Case:

Monitoring, Guardrailing, and Improvements

Use Case:

Monitoring, Guardrailing, and Improvements

Highlights

  • Real-Time Degradation Detection - continuously track key metrics like accuracy, relevance, safety, and hallucination rates to detect when RAG/LLM outputs begin drifting, before they impact users or business outcomes.
  • Diagnose by leveraging deep telemetry across queries and responses to pinpoint root causes of quality issues, optimize retrieval and LLM configurations, and accelerate resolution cycles.
  • Iterate on Model & UX Improvement by closing the feedback loop, capturing real-world usage data, refining model performance, and enhancing user experience.
  • Compliance-Ready Logging & Audity: Log every interaction and response with full traceability, especially critical for regulated industries like healthcare and finance.

Track What Matters Most

Not all metrics are created equal. With AIMon, you can monitor the most business-critical indicators and detect when models receive risky inputs or respond with poor-quality outputs. Our platform helps you catch subtle declines before they become costly issues, ensuring your AI maintains performance in dynamic environments.

Telemetry for Fast Diagnosis and Auditability

Our system captures granular telemetry across every interaction. From query patterns to model responses, we log and surface the data you need to quickly identify root causes and resolve performance issues. For highly regulated industries, our logging system ensures auditability of every response ensuring compliance, governance, and operational trust.

Iterative Improvement & Feedback Loops

Shipping AI products isn’t a one-and-done process. AIMon supports an iterative development cycle where teams gather real-world feedback, analyze performance, and push targeted improvements. Whether it’s tuning LLMs, refining retrieval strategies, or adjusting scoring thresholds, our tools help you evolve your app continuously with explainability and precision.

Deliver Consistent Quality at Scale

Users expect consistent responses across sessions, use cases, and user segments. AIMon’s monitoring framework ensures that your models deliver predictable, context-aware outputs—day after day. Maintain alignment with brand tone, regulatory guidelines, and functional expectations with our proactive quality controls.

Ship Faster with Confidence

Every AI feature, model update, or prompt change is logged and tracked. This gives your team the confidence to ship improvements quickly—knowing that performance, safety, and quality can be measured and validated in real time. For compliance-heavy industries like healthcare, finance, or legal, complete audit trails ensure you’re always prepared for review.

Powered by Purpose-Built, Proprietary Technology

Unlike generic monitoring tools, AIMon is purpose-built for LLM and RAG systems. From identifying response drift to auto-alerting on hallucination spikes, our platform powers the most demanding production AI workflows. Whether you’re a Fortune 200 enterprise or a fast-scaling startup, AIMon helps you deliver AI apps that are reliable, explainable, and continuously improving.

About AIMon

AIMon helps you build more deterministic Generative AI Apps. It offers specialized tools for monitoring and improving the quality of outputs from large language models (LLMs). Leveraging proprietary technology, AIMon identifies and helps mitigate issues like hallucinations, instruction deviation, and RAG retrieval problems. These tools are accessible through APIs and SDKs, enabling offline analysis real-time monitoring of LLM quality issues.