Rhizome

Claude is a brilliant general assistant. Rhizome is a focused, AI regulatory coworker.

When there are nine figures riding on the program, the research underneath the decision needs high-trust, traceable machinery that Claude does not ship with

How they differ

Claude might be the best general-purpose assistant there is. Writing, reasoning, long documents, code: teams are right to standardize on it. But general-purpose is a design goal, and it pulls in a different direction than “help me make a drug or device decision I can defend to a regulator.”

Nothing from memory. General models rely on memory for a real fraction of what they tell you, and the failure is sneaky. Within a single answer, one sentence can come from memory while the sentences before and after it are properly sourced. You can't see the seam. For everyday work that's fine. For a position you're going to argue to FDA, one unsourced sentence is the whole problem.

We build our agents around the opposite rule: nothing gets substantiated from memory. Every fact has to be pulled from a primary-source document, and we run benchmarks specifically on that discipline. That rule makes answers slower and much more expensive to produce, a trade a general assistant can't make, because its users expect a response in seconds and its cost structure assumes one. Ours can. Slow-and-right is the entire product.

The record Claude doesn't ship with. Where should those facts come from? The material that actually decides regulatory questions — Drugs@FDA, EPARs, clinicaltrials.gov and its protocols, guidance libraries, enforcement records — is famously hostile to software. Much of it has no machine-readable text at all; the substance sits in scanned, image-only PDFs. That's not a Claude flaw. No web browse, however good, reaches what was never indexed.

Reaching it is our whole job: as of August 2026 Rhizome maintains >75 health-authority databases across >12 markets, each one processed down to the line and the image so nothing hides in a scan: >45 million documents our agents can search at will. The number grows constantly.

Exhaustive research. Ask Claude alone for precedent and you get a thin sample: two or three examples when the record holds three dozen, and rarely anything from authorities that don't surface in a web search. A hard question on Rhizome will chew through several hundred sources, sometimes a few thousand, because what you're really asking is “is there a precedent we're missing?”, and no sample can answer that.

Traceability. Claude cites documents or web pages, when it cites at all. Rhizome's citations resolve to the passage itself: click one and you're reading the exact lines it came from. When the claim you're checking lives somewhere inside a review that runs to hundreds of pages, that difference is your afternoon.

When Rhizome is the better choice

Precedent that has to be complete enough to build strategy or walk into an agency meeting
Multi-authority or deep-document questions
Output you'll verify page-by-page before you co-sign it
You want Claude's UX with grounding Claude alone can't give you — connect Rhizome over MCP and stay in the chat you like

When Claude is the better choice

Almost everything that isn't “cite the health-authority record”
Writing and restructuring text you already trust
Code, analysis, internal documents you've provided
High-level questions where “reasonably good” is enough and you're not building a filing argument

One honest nuance: Claude Projects loaded with your documents can go genuinely deep on that pack. That's a different job from scanning the public record at scale, and a good reason to run both. The deeper split: Claude is the right home for what makes your company yours: your documents, your code, your science. The public record isn't yours, and nobody differentiates on reading it. It just has to be right.

Ask a precedent question. Open the sources.

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