LLMValidate.ai
Open evaluation framework for LLMs and RAG pipelines.
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LLMValidate.ai evaluates LLM and RAG applications before and after they go live. It uses a self-hosted vLLM judge, local small models such as toxic-bert for safety checks, and custom scoring modules, and it plugs into any RAG pipeline over HTTP. Built by testAIng.com (AiEnsured), an ISO/IEC 42001 certified AI assurance company.
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PH · launched Oct 22, 2026 · 2 upvotes (top 22%)
- Horizontal
- Observability & eval
- Developer
- AI-native
- Hobby / open-source project
- Developer Tools
- Artificial Intelligence
Similar launches
See all 205 similar launches →Could you build this?
Yes An evaluation harness that calls a judge model, runs local classifiers like toxic-bert, applies custom scoring modules, and exposes an HTTP interface is standard software engineering. Its components are well-documented open-source tools.
What it would actually take: Use a Python backend with an evaluation pipeline that sends test cases to the target RAG app over HTTP, scores outputs with a self-hosted vLLM judge and local models like toxic-bert, and reports results on a dashboard. The real difficulty is choosing well-calibrated metrics and test suites, which benefits from ML evaluation expertise but is not a blocker for a working version.
Competitors
Other products that read as similar to this one : 205 launches clear the similarity bar, closest 8 shown.
Attention rank: #36 of 206 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).
Launched 356 days after the earliest competitor.
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Other launches for this product
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