Rhizome AI

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It takes 500,000 days of office work to bring a drug to market. We want to make it 5. To get there, we need agents doing most of the work.

Today, our research agent is the best way to know what the FDA thinks. Users ask a question and get an answer backed by up to 1,000 documents, where each statement has a citation.

It’s the best because we have the best retrieval engine. We’ve tuned it on our life science-specific dataset, and we find what others miss.

As more teams use Rhizome, we gain more data on what regulatory professionals actually need, which makes retrieval even better. This flywheel is how we become the retrieval engine that powers all human and agent work in life sciences.

Chetan started his career as a research engineer, but quickly realized he enjoyed building more than research. He joined EvolutionaryScale as their sole founding product engineer, launching their developer-scientist platform and scaling to tens of thousands of users and billions of API calls. He was also #16 at Instabase helping banks with document processing, closing $7m as the technical closer.

Agents can do magical things today, but most in life sciences only use them to edit emails. Agents are missing the context they need to 100x the number of drugs we can bring to market. Rhizome AI is focused on that critical problem.

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