BioStack, a healthcare technology company, announced today that it’s launching a data infrastructure network to power the next era of medicine. It spans a global footprint across the U.S., India, Brazil, and Argentina with over 100 million de-identified patient records. By connecting fragmented clinical information, BioStack gives AI and biotech companies the high-quality data needed to train models that understand how disease unfolds, how treatments work, and what drives patient outcomes.
The company also announced $9.5 million in seed funding led by Peak XV, Afore Capital, DCVC, Emerson Collective, SV Angel, Verdict Capital, Streamlined Ventures, and Y Combinator. The round will support BioStack’s continued expansion across the United States and international markets, development of its technology platform and growth of its engineering and research teams.
Today, patient histories and other clinical data are often fragmented across hospitals, providers and technology systems, leaving clinicians without a complete picture of a patient’s treatment. BioStack creates workflows that bring together clinical information across disparate health systems and geographies. Connecting notes, labs, imaging, medications, treatments and outcomes, BioStack provides a more comprehensive view of the patient and informs population-level and hospital-level discovery.
“Collecting every event linked to each patient enables a view of what happens at each stage of a patient’s journey. 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.”
-Sanat Mishra, co-founder and CEO of BioStack
In addition to creating custom workflows that protect patient privacy and are based on individual provider protocols, BioStack creates proprietary datasets from de-identified data that it collects from each provider system. These datasets can support medical research, drug development and the training and evaluation of healthcare AI models.
It connects biological and clinical data with treatment histories and long-term outcomes. This helps researchers understand what happened to a patient and how different interventions affected their health over time.
BioStack creates a feedback loop between clinical care and medical innovation. As more longitudinal patient information becomes available, researchers and AI developers can gain a richer understanding of disease progression and treatment response. Healthcare providers can benefit from new insights and more personalized approaches to care.
In India, BioStack is helping connect cancer patients with an investigational cancer vaccine program. Patients’ clinical data can support biotech companies’ development efforts, while eligible patients may gain access to highly personalized investigational treatments.
BioStack has combined more than several hundred thousand fragmented X-Rays, MRIs, CT scans with other pathology and clinical records. The resulting dataset provides a powerful resource for training AI agents to help clinicians evaluate treatment options and likely patient outcomes.
“The next frontier of healthcare AI will depend not only on better models, but on access to high-quality, longitudinal data that reflects how patients are treated over time. Sanat and the BioStack team are building critical infrastructure that connects fragmented clinical information and transforms it into a valuable resource for clinicians, researchers and AI developers. We believe BioStack has the potential to become an important data layer for the next generation of medical AI.”
-Pushpak Kedia, Vice President, Peak XV
BioStack currently works with hospitals across the U.S., Brazil, India and Argentina, giving the company access to a diverse patient population and healthcare environments. Its platform is designed to support applications including medical AI model development and evaluation, clinical research, disease modeling, biomarker discovery, patient stratification and treatment-response analysis.
