Products/Artificial Intelligence, APIs & Integrations, Developer Tools/5.Wauldo Guard

5.Wauldo Guard

Every RAG framework hallucinates. We catch them with a number.

Artificial Intelligence, APIs & Integrations, Developer ToolsNumeric trust score (confidence 0-1)Source-grounded claims mapped to exact passageDeterministic verification (Rust + regex, not LLM-as-judge)Open leaderboard (6 frameworks, 70 tests)3-line install: pip install wauldoLive trust score tool (no signup required)

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Our Take

Wauldo Guard is the move if you're building with RAG and don't want your users getting fed hallucinated nonsense. They're putting their money where their mouth is — checking outputs against source documents using Rust and regex, not bouncing answers off another LLM to judge itself, which is genuinely clever — and the leaderboard doesn't lie: 4% hallucation versus 14-54% across LangChain, LlamaIndex, Haystack, and CrewAI. Free tier's there, three-line pip install, and they're testing daily on 70 adversarial prompts covering prompt injection, source contradictions, and factual recall. If you're shipping AI to real users, this is the dark horse that'll actually save your reputation.

LLM verification layer that checks every LLM claim against source data before responses reach users. Provides numeric trust scores [0,1] for responses.

Problem It Solves

All existing RAG frameworks hallucinate (14-54% hallucation rates tested on 70 adversarial prompts). Wauldo Guard achieves only 4% hallucination rate.

Target Customer

AI developers building with RAG frameworks, companies requiring AI safety and hallucination detection, developers integrating LLMs into applications.

Use Cases

Verify LLM answers against source documents, Detect hallucinations in AI responses, Production-grade LLM response validation, Trust scoring for AI-generated content

Pricing Details

Free $0 · Guard $9/mo · Pro $29/mo · Scale $99/mo · Enterprise custom

Free Tier

Yes, $0

Differentiator

Only 4% hallucination vs 14-54% for other frameworks (LangChain 40%, LlamaIndex 54%, Haystack 40%, CrewAI 29%, Vanilla LLM 14%). Uses deterministic Rust+regex verification, not LLM-as-judge.

Why Now

Live daily refresh tested on 70 adversarial prompts covering prompt injection, source contradictions, out-of-scope refusal, and factual recall.

Traction

Notable Metrics: 7 upvotes on OpenHunts, 67/70 tests passed (4% hallucination rate)

Key Facts

The people behind 5.Wauldo Guard

Zin Benzin

profile

Links

Website GitHub Source: openhunts

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