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Agnost AI

Catch agent failures your evals miss

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Agnost AI analyzes conversations between users and your production AI agents and discovers: silent failures, agent behavior drift, hallucinations, user frustration, hidden feature requests, and churn signals. It groups them into recurring patterns, shows the exact users and conversations behind each insight, and turns them into evals and fixes.

PH · launched Aug 25, 2026 · 289 upvotes (top 39%) · 1 view

Niche: ai agent evaluation platforms · 183 launches, 9 in the last 7 days ▼ -44% · Explore this niche →

Category and tags

  • Horizontal
  • Observability & eval
  • Developer
  • AI-native
  • Commercial product
  • Analytics
  • Developer Tools
  • Artificial Intelligence

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Could you build this?

Partial The dashboard, SDK, and LLM-as-a-judge evaluations are easily vibe-coded, but reliably auto-clustering large volumes of conversations to detect subtle drift and silent failures requires specialized NLP pipelines and high-throughput data infrastructure.

What it would actually take: The architecture needs a high-throughput event streaming ingestion pipeline (e.g., Kafka or ClickHouse), embedding generation services, and unsupervised clustering algorithms (such as HDBSCAN with dynamic topic modeling) optimized to run over streaming conversation graphs. The difficult engineering lies in scalable real-time drift detection, reducing false-positive hallucination detections, and running cost-effective evals across millions of conversational tokens.

Competitors

Other products that read as similar to this one : 1519 launches clear the similarity bar, closest 8 shown.

Attention rank: #871 of 1520 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 298 days after the earliest competitor.

The niche, labels, vibe code rating and competitor comparison on this page are analysis by Nicheloom. If you use them, please credit nicheloom.com. How you may use our data.