Octozi, a New York City-based artificial intelligence company that automates clinical development workflows for pharmaceutical sponsors, has raised 3 million dollars in seed funding. Surface Ventures led the round, with participation from Remarkable Ventures, building on a prior strategic investment from the venture arm of Swiss pharmaceutical company Debiopharm. The capital will be used to expand Octozi’s agentic AI platform and deepen its integrations with clinical systems used by pharmaceutical, biotech and medtech companies.
Clinical trials generate large volumes of data that must be cleaned, reconciled, and reviewed before regulators will approve new therapies. Much of this work is still performed manually by data managers, medical monitors, and safety teams, which adds time, cost, and operational risk to drug development. Octozi’s platform integrates with existing clinical systems and uses a human‑in‑the‑loop design, keeping study teams in control while automating tasks such as data cleaning, data review, reconciliation and reporting. The technology combines large language models with deterministic clinical algorithms and external medical knowledge so outputs reflect clinical context—for example, distinguishing an expected drop in platelet counts after chemotherapy from discrepant data that warrants investigation.
The platform already supports Phase III trials, which are among the largest and most complex stages of clinical development and can involve thousands of patients. In a controlled study described in a published research paper, AI assistance from Octozi increased data‑cleaning throughput roughly six‑fold, reduced reviewer error rates from about 54.7% to 8.5%, and lowered false‑positive queries by roughly fifteen‑fold. An accompanying economic analysis of a representative Phase III oncology trial estimated potential savings of more than 5 million dollars per study, primarily because databases could be locked sooner and timelines compressed.
Octozi positions its platform as an operational layer designed around how clinical teams actually work, rather than as a dashboard that leaves interpretation to human reviewers. By embedding AI into existing workflows with human oversight, the company aims to reduce bottlenecks in data operations, improve the quality of submissions to regulators and shorten the time it takes to move data through critical review steps. Investors see the technology as a way to improve data quality, ease pressure on clinical and data teams and potentially speed time to market for life‑saving therapies.
KEY QUOTES:
“Most tools in this space put trial data on a dashboard and leave the analysis to clinical teams. Octozi was built to perform that work alongside the people who own the data, with the human in control and the model handling tasks that previously took weeks of manual effort.”
“Clinical development is one of the most expensive and time-consuming processes in any industry, and the data operations layer underneath it has barely changed in decades. We think purpose-built AI, designed around how clinical teams actually work, can compress timelines, reduce risk, and bring down cost across the entire development cycle.”
Amit Patel, Co‑Founder and CEO, Octozi
“Octozi brings value to pharmaceutical companies in multiple ways. It improves the quality of data submitted to regulatory bodies; it helps clinical development and data teams with their day to day work, allowing them to be less of a bottleneck in all the trials they may be managing; and it speeds up the time on specific tasks, which allow pharmaceutical companies to get data out faster to regulators, potentially speeding up time to market for life saving therapies.”
Gyan Kapur, Managing Partner, Surface Ventures
