ChatGPT is a general assistant. Rhizome is a AI regulatory coworker.

When you're focused on everything, you're not really focused on anything. ChatGPT is designed to be that general purpose assistant, and it's phenomenal at it. But there are many obvious things that should be different about an AI agent helping make >$100m drug or device decisions.

Relies on the facts. Good enough is rarely good enough in life sciences. A wrong decision could lead one to question a clinical trial's outcome. Poor advocacy for your position could lead FDA reviewers to conclude the opposite is true and harden their position during subsequent interactions. AI models can help you get there, but only if they give you fully trustworthy, hallucination-free advice.

Rhizome does this by pushing our agents to only rely on primary source data. Nothing can be substantiated from agent memory, and we explicitly benchmark our agents for this capability.

General purpose products (like ChatGPT) cannot do this. General consumers (most of their user bases and customers) hate waiting. They want an answer and they want it immediately.

It's also dramatically more expensive to run an AI agent this way. For the big labs, their consumer business costs have to be covered by ads. That's just not possible if they're exhaustively researching and thinking before each answer.

Direct integrations to industry databases. OK — so even if our agent has to source all facts from primary sources, where should those sources come from? Our agents shouldn't just trust anything on the internet.

ChatGPT / Claude / etc. often do. Blogs, investor presentations, trade press, SEO AI slop are all given relatively even weight. Even if you ask it to only look in regulator guidance or review documents, it'll only do that some of the time.

It's not necessarily these products' fault. The databases that truly drive regulatory decisions in this industry — drugs@fda, guidances, clinicaltrials.gov (and its protocols), standards, etc. — are not available in formats easy for computers to search and understand. Oftentimes they don't even have machine-readable text, as the data is stored in image or image-only PDF form.

Rhizome fixes all of these challenges. We have >75 health authority databases across >12 markets (as of August 2026 — this increases all the time). We're on pace to support >150 HA databases and >25 markets by EOY. Each line of text in a regulation is ingested, each image on a document is processed with the best AI models to understand its exact contents.

This is the key repository our agents pull their data from. >45 million documents, made available for our agents to query exhaustively.

Exhaustive research. ChatGPT often answers off of 5–10 sources. Rhizome looks at hundreds to thousands frequently.

Part of this is just due to design. When an agent needs to get every fact it's relying on from primary sources, it needs to do tons of research. When you ask about stability testing, Rhizome will reference guidances, regulations, SBOAs, 483s, warning letters, and more, to give you a complete picture.

Our search infrastructure fully handles this as well: it supports >50 search requests per second.

Traceability. ChatGPT cites documents or web pages. Rhizome cites exact passages.

Getting thrown into a 500-page SBOA document hunting for where the AI might have read a specific claim is a frustrating task. This is exactly what ChatGPT will do. Again, this is because consumers don't really care about the sources. They want a good enough answer and to move on.

But for the scientist trying to convince the FDA of a certain preclinical plan, they need to know they're citing accurate precedent. Rhizome helps them confirm this.

Each citation in Rhizome is to an exact page or set of paragraphs. We make it really easy to check by taking you to the exact citation when you click any of our citations.