Medical AI is only as good as the clinical data it learns from, and that data is notoriously scattered. BioStack, an AI-driven healthtech startup founded in 2025 by Sanat Mishra and Parth Patwa, has raised $9.5 million (about ₹90.4 crore) in a seed round to build what it describes as the data infrastructure for the next generation of medical AI.

The round drew participation from Peak XV Partners, Afore Capital, DCVC, Emerson Collective, SV Angel, Verdict Capital, Streamlined Ventures and Y Combinator, according to Inc42.

Turning fragmented records into AI-ready datasets

BioStack brings together clinical information that typically lives in separate systems, including electronic health records, medical imaging, clinical notes and medication histories. It then structures this information into proprietary, de-identified datasets for research, biotechnology and the development and training of medical AI models.

“We’re building the infrastructure that connects all of the clinical information and makes it useful, both for clinicians making decisions today and for the researchers and AI developers building the future of medicine,” said Sanat Mishra, co-founder and CEO of BioStack.

The company says it has processed around 10 crore de-identified patient records, several hundred thousand X-rays, MRIs and CT scans, and several million telehealth audio transcripts so far, with custom workflows designed to protect patient privacy. Use cases it supports include AI model evaluation, disease modelling, biomarker discovery, patient stratification and treatment-response analysis.

Where the money goes

BioStack currently works with multiple hospitals in the US, Brazil and Argentina. The new capital will be used to deepen its presence in the US and expand across international markets including India, Brazil and Argentina, scale its technology stack, and hire across engineering and research. In India, the startup is also helping connect cancer patients with an investigational cancer vaccine programme.

India’s growing role in AI training data

The raise lands as India emerges as a significant source of training data for AI. A wave of startups, including Awign, Objectways and Human Archive, is building pipelines that capture real-world activity and supply datasets to frontier AI labs and robotics companies. India’s AI training dataset market is projected to become a $1.3 billion opportunity by 2033.

For healthcare, the stakes are higher than in most sectors. Clinical AI demands data that is representative, well-labelled and handled under strict privacy safeguards. Startups that can assemble such datasets responsibly, across geographies and modalities, are positioning themselves as critical infrastructure for the medical AI stack, and the backing BioStack has attracted suggests investors see that layer as a durable opportunity.

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