Alternatives
Products that do what WithAccurateFood does
RAG, PubMed, No Hallucination
- 1OS
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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Turn PDFs into courses with AI without irrelevant additions
2025
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- 7FA
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
- 8FM
Hi HN, We've been frustrated with how confidently LLMs hallucinate—a dangerous flaw in high-stakes domains like health and medicine. The standard "I am not an expert" disclaimer feels insufficient since we all ignore those statements. Our approach is a RAG/agentic system built to solve this. It runs on ~40M+ scientific papers, but goes beyond simple retrieval. A multi-agent workflow decomposes queries, cross-references claims against multiple sources, and synthesizes answers, ensuring every key statement is cited directly from the literature. Beyond the literature, our agent system has…
2025 · my-openhealth.com
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Gen AI tools for factual, source-based, & up-to-date content
2023
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Trustworthy AI medical insights with zero-hallucination RAG.
May 2026 · dr-owl-medical-rag.vercel.app
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Hey HN! Mustafa, Lizzie, and Varun here from NomadicML (https://nomadicml.com). We’re excited to show you Nomadic (https://github.com/nomadic-ml/nomadic): a platform focused on parameter search to continuously optimize AI systems. Here’s a simple demo notebook where you get the best-performing, statistically significant configurations for your RAG — and improve hallucination metrics by 4X in just 5 minutes — with a single Nomadic experiment: https://tinyurl.com/4xmaryyw Our lightweight library is now live on PyPI (`pip install nomadic`). Try one…
2024
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AI research tool where YOU choose which publishers to trust
Mar 2026 · hallucinationbuster.com
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The first GPT-based solution that uses hallucinations from LLMs for divergent thinking to generate new and novel ideas. Hallucinations are often seen as a negative thing, but what if they could be used for our advantage? dreamGPT is here to show you how. The goal of dreamGPT is to explore as many possibilities as possible, as opposed to most other GPT-based solutions which are focused on solving specific problems.
2023 · github.com
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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
- 22AF
I have some chronic medical conditions, and spend a lot of time asking about different drugs and supplements. Wanted to create a resource that others might get value from. It's trained to always provide citations, and to urge people to see their doctor before making major decisions. Open for feedback.
2024 · agenthost.ai
- 23TV
Hey HN, Joe and Ethan from Tonic.ai here. We just released a new open-source python package for evaluating the performance of Retrieval Augmented Generation (RAG) systems. Earlier this year, we started developing a RAG-powered app to enable companies to talk to their free-text data safely. During our experimentation, however, we realized that using such a new method meant that there weren’t industry-standards for evaluation metrics to measure the accuracy of RAG performance. We built Tonic Validate Metrics (tvalmetrics, for short) to easily calculate the benchmarks we needed to meet in…
2023 · github.com
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