Alternatives
Products that do what Truth Mirror does
Real-time AI hallucination detection. Don't trust, verify.
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This is a quick prototype I built for semantic search and factual question answering using embeddings and GPT-3. It tries to solve the LLM hallucination issue by guiding it only to answer questions from the given context instead of making things up. If you ask something not covered in an episode, it should say that it doesn't know rather than providing a plausible, but potentially incorrect response. It uses Whisper to transcribe, text-embedding-ada-002 to embed, Pinecone.io to search, and text-davinci-003 to generate the answer. More examples and explanations here:…
2022 · huberman.rile.yt
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Hi all! This morning, we released a new Apache 2.0 licensed model on HuggingFace for detecting hallucinations in retrieval augmented generation (RAG) systems. What we've found is that even when given a "simple" instruction like "summarize the following news article," every LLM that's available hallucinates to some extent, making up details that never existed in the source article -- and some of them quite a bit. As a RAG provider and proponents of ethical AI, we want to see LLMs get better at this. We've published an open source model, a blog more thoroughly describing our methodology (and…
2023 · vectara.com
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Stop BS in real-time with AI that fact-checks as you listen
Mar 2026 · factsnobullshit.up.railway.app
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Turn PDFs into courses with AI without irrelevant additions
2025
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GhostDesk▲88Your invisible AI co-pilot for interviews & meetings
Apr 2026 · ghostdesk-iota.vercel.app
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Catch AI's made-up facts before you publish them
Jul 2026 · aitoolcritic.com
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AI research tool where YOU choose which publishers to trust
Mar 2026 · hallucinationbuster.com
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Verify reality. Detect synthetic media in seconds.
May 2026 · truthguard-ai-deepfake.lovable.app
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Hi HN. I'm Ken, a 20-year-old Stanford CS student. I built Sup AI. I started working on this because no single AI model is right all the time, but their errors don’t strongly correlate. In other words, models often make unique mistakes relative to other models. So I run multiple models in parallel and synthesize the outputs by weighting segments based on confidence. Low entropy in the output token probability distributions correlates with accuracy. High entropy is often where hallucinations begin. My dad Scott (AI Research Scientist at TRI) is my research partner on this. He sends me papers…
Mar 2026 · sup.ai
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We built tooling that connects LLMs directly to case law databases with citation verification to address hallucination in legal AI. Think of it as giving the model access to actual legal sources instead of relying on training data.
Feb 2026 · openjuris.org
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