Independent, multi-model fact-checking API for AI workflows
Lenz is an AI fact-checking API for products that cannot afford to hallucinate. It extracts verifiable claims from any text, then checks each one: searching independent sources, running multi-model debate, and routing through a review panel — returning a scored verdict with every source, argument, and step visible. Most AI tools give you one model's best guess from memory. Lenz ensures no single model's blind spots drive the conclusion. Available as API and MCP. Try it free at lenz.io/ph
Kosta here, co-founder of Lenz. Many businesses ship AI-generated content to their customers. Some of those use cases could benefit from factual verification of that AI output. That's why we built Lenz, packaged it as an API/SDK, and made it available across multiple platforms (n8n, Zapier, MCP, CLI), so people can easily integrate it into their workflows. Lenz verdicts come with a full audit trail - sources, citations, reasoning, confidence.
How Lenz is different than just asking a model:
(1) separate evidence gathering step (with source ratings) that doesn't rely on the model's memory or retrieval capabilities
(2) multi-vendor, multi-model approach to address single-model biases
(3) multi-round adversarial debate to crystallize the strongest for/against arguments
(4) multi-model jury reviewing the evidence and the debates across multiple axes
Key API primitives: /extract - extracts the factual claims from a text; /assess - quick assessment of a claim; /verify - the full deep claim verification; /ask - follow-up post-verification questions.
We measured the level of disagreement between the individual frontier models: on 23% of real-world claims, they disagree significantly, which sets the floor of the error Lenz is built to address.
Hope you find this useful. Let me know either way :)
About Lenz on Product Hunt
“Independent, multi-model fact-checking API for AI workflows”
Lenz launched on Product Hunt on August 27th, 2026 and earned 252 upvotes and 36 comments, earning #3 Product of the Day. Lenz is an AI fact-checking API for products that cannot afford to hallucinate. It extracts verifiable claims from any text, then checks each one: searching independent sources, running multi-model debate, and routing through a review panel — returning a scored verdict with every source, argument, and step visible. Most AI tools give you one model's best guess from memory. Lenz ensures no single model's blind spots drive the conclusion. Available as API and MCP. Try it free at lenz.io/ph
On the analytics side, Lenz competes within Artificial Intelligence — topics that collectively have 477.2k followers on Product Hunt. The dashboard above tracks how Lenz performed against the three products that launched closest to it on the same day.
Who hunted Lenz?
Lenz was hunted by Kosta Jordanov. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Lenz including community comment highlights and product details, visit the product overview.
Kosta Jordanov
Kosta here, co-founder of Lenz. Many businesses ship AI-generated content to their customers. Some of those use cases could benefit from factual verification of that AI output. That's why we built Lenz, packaged it as an API/SDK, and made it available across multiple platforms (n8n, Zapier, MCP, CLI), so people can easily integrate it into their workflows. Lenz verdicts come with a full audit trail - sources, citations, reasoning, confidence.
How Lenz is different than just asking a model:
(1) separate evidence gathering step (with source ratings) that doesn't rely on the model's memory or retrieval capabilities
(2) multi-vendor, multi-model approach to address single-model biases
(3) multi-round adversarial debate to crystallize the strongest for/against arguments
(4) multi-model jury reviewing the evidence and the debates across multiple axes
Key API primitives: /extract - extracts the factual claims from a text; /assess - quick assessment of a claim; /verify - the full deep claim verification; /ask - follow-up post-verification questions.
We measured the level of disagreement between the individual frontier models: on 23% of real-world claims, they disagree significantly, which sets the floor of the error Lenz is built to address.
To try a Lenz verification via the UI: lenz.io/verify
More about the LLM disagreement research: lenz.io/research/llm-disagreement
To integrate Lenz: lenz.io/integrations
GitHub: github.com/lenzhq
Hope you find this useful. Let me know either way :)