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Metriport Secures $26 Million to Automate Medical Record Synthesis

San Francisco-based Metriport has raised $26 million to scale its open-source infrastructure, which aggregates fragmented patient records into actionable insights for clinicians. The funding round, led by Matrix, brings the startup’s total capital to $28.4 million as it seeks to replace outdated fax-based record retrieval with automated, real-time data integration.

Bio & NewsAugust 27, 20261,036 reads0

Healthcare providers have long struggled with the administrative burden of gathering patient histories from disparate sources, a process that frequently relies on manual requests and patient recall. Metriport addresses this by pulling records from pharmacies, hospitals, and specialists into a unified data model. The platform then uses standardized APIs and AI-driven summarization to surface relevant information directly within existing electronic health record systems.

Major organizations, including Amazon One Medical and Sollis Health, have already adopted the technology to reduce diagnostic delays and prevent redundant testing. Dr. Scott Braunstein, CMO at Sollis Health, noted that the platform’s ability to instantly retrieve specific operative reports—such as past endoscopy findings—allows clinicians to initiate treatment immediately rather than waiting weeks for faxed documents. Beyond mere aggregation, the company emphasizes a rigorous, open-source approach to data transformation, aiming to provide transparency that proprietary "black box" systems often lack.

With its recent HITRUST r2 certification, the company plans to deploy this new capital to expand its machine learning and agentic capabilities. According to CEO Dima Goncharov, the goal is to shift industry standards so that providers no longer make decisions without the full context of a patient's medical history. By vetting every organization granted access to its network, Metriport intends to balance rapid scalability with the high-stakes security requirements inherent in sensitive health data.

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