Healthcare organizations often struggle to leverage their clinical data for AI applications due to unstructured formats and lack of proper labeling. Nimblemind.ai, a Chicago-based AI-powered data infrastructure platform, announced on March 14, 2025 that it secured $2.5 million in funding to address this challenge by helping providers structure and utilize their clinical data.
Key Points
- The funding round was led by Bread & Butter Ventures with participation from Great Oaks Venture Capital, SpringTime Ventures, Stone Mountain Ventures, Victorum Capital, Techstars, and strategic healthcare angel investors.
- The startup aims to make unstructured healthcare data AI-ready through curation and labeling of clinical datasets.
- Nimblemind.ai’s platform enables healthcare providers to transform raw patient data into structured, AI-ready formats while maintaining data sovereignty and compliance.
- The startup has established partnerships with multiple healthcare organizations in the US and Asia.
- APT Foundation reports using the system to identify patient interventions more effectively by organizing data from electronic medical records, patient surveys, and wearable devices.
- Nimblemind.ai plans to use the funding to expand its specialty-specific AI models, enhance platform capabilities, and onboard additional healthcare providers.
- The healthcare data structuring market includes established players such as IQVIA and Health Catalyst, which were named among Newsweek’s top 50 healthcare data analytics companies in 2024.
Nimblemind.ai’s approach targets healthcare providers seeking to implement AI solutions while maintaining control over their data, addressing both clinical decision support and operational efficiency needs.
The Data
- Funding amount: $2.5 million total raised in current round.
- Geographic reach: Partnerships established in US and Asia markets.
- Data sources supported: Electronic medical records (EMR), patient surveys, and wearable devices.
- The recent announcement did not provide metrics on platform performance, user adoption rates, or specific clinical outcomes achieved.
- Past estimates have shown that hospitals are generating approximately 137 terabytes of data daily. Meanwhile, the healthcare industry lacks standard procedures to structure and organize its vast amounts of unstructured data.
Industry Context
We are at an inflection point where AI can revolutionize healthcare, but without well-structured, specialty-specific data, its full potential remains untapped.
Pi Zonooz, CEO and Co-Founder of Nimblemind.ai
Nimblemind.ai positions its platform as addressing a fundamental barrier to healthcare AI adoption: the challenge of converting unstructured clinical data into formats suitable for machine learning applications. Healthcare providers could potentially use the structured data for clinical decision support, operational improvements, and what the company describes as “non-clinical revenue opportunities,” though specific examples of these opportunities were not detailed in the recent fundraising announcement.
Mary Grove of Bread & Butter Ventures, which led the recent round, characterized healthcare transformation as potentially “the single most significant application of artificial intelligence in our time.”
