Katalyze AI

Investigate a deviation, understand a change in yield, examine raw materials, or prepare a transfer. Katalyze connects the evidence.

Connectors bring relevant system data, scientific datasets, research publications and other academic sources into the Katalyze Context Layer.

Turn batch records, certificates of analysis and other records from suppliers, CROs, CDMOs and your labs into contextualized, source-linked data.

Interactive pieces from Katalyze, starting with a biomanufacturing suite whose equipment answers for itself, from its own records.

What AI agents can do in GMP operations, what FDA, EMA and the EU GMP Annex 22 draft expect, and the controls a quality team should look for.

The pharma and biotech teams on Katalyze: the outcomes they report and the nine teams the platform is built for, from MSAT to 503B facilities.

The long-form guides, one question each.

Why plant data in one place is still not usable together, what an ontology and a knowledge graph each do, and what source grounding means in practice.

Already deployed across 5 of the 20 largest global pharma companies, Katalyze has enabled pharma teams to deliver 10 million medication doses to patients.

Releases, coverage and the press kit from Katalyze, the agentic infrastructure for life sciences, which connects pharma documents and system data.

Katalyze hires people in New York City, San Francisco, and Toronto to work on halving the time and cost of bringing new lifesaving drugs to market by 2030.

Bring Katalyze into a biopharma manufacturer's operation, starting with one high-value use case, and stay with the team until it runs every day.

Build the applications scientists and engineers in biopharma manufacturing use to ask their records questions, check the sources and act on the answers.

Katalyze is priced per workspace, not per seat. A workspace is one molecule, one site or one trial, with its own governed context.

More than a hundred scientists and engineers from across pharma, from companies such as Pfizer, Sanofi and Lilly, help shape Katalyze.

Katalyze aims to reduce the time and cost of bringing a new lifesaving medication to market by half by 2030.

Reach the Katalyze team about press, investment, partnerships or anything else. Offices in San Francisco, Toronto and New York City.

The page explains Katalyze’s purpose, how it integrates with existing systems, and how Document Intelligence and the Context Layer process data.

Katalyze connects documents and system data across pharma operations into source-grounded context, then applies governed agentic solutions to work on it.

Katalyze AI’s privacy policy describes how it collects, uses, and shares information through its services.