Artificial intelligence startup Keebler Health has raised $16 million in Series A funding to continue building an AI-powered infrastructure for value-based care.
Flare Capital Partners led the Series A round, with participation from Sands Capital, Tau Ventures, and existing investors including Freestyle Capital, Underdog Labs, and MBX Capital. Additional investors in this round include Everywhere Ventures, New Stack Ventures, Tweener Fund, Aviano Ventures, and Hustle Fund, according to a press release.
Isaac Park, CEO and co-founder of Keebler Health, said the startup has raised $23 million to date.
Risk adjustment remains constrained by fragmented medical data, with the most important patient information existing outside of coded fields, executives said.
Keebler Health uses an LLM-native risk adjustment platform built to process unstructured clinical documents. The tool creates accurate and complete Hierarchical Condition Category (HCC) coding, providing clinicians with actionable insights in the clinical setting, executives said.
“As we were exploring the technology frontier, we realized that risk adjustment was actually a really great place to start impacting change in these kinds of technologies that we leverage,” Park told Fierce Healthcare in an exclusive interview about the Series A funding round.
Keebler Health executives said a central challenge in risk adjustment is the gap between what is documented and what is captured in the coded field. Approximately 80% of medical information is unstructured and resides in descriptions, imaging reports, and discharge summaries rather than coded fields. And even structured records are often incomplete. A study published in the Journal of the American Medical Informatics Association found that only 59.4% of chronic conditions were captured consistently across electronic medical record sources. The result is a systemic gap in risk understanding and reimbursement accuracy.
“What stood out to us about Keibler was how clearly the team addressed the long-standing limitations of health data,” Ian Chan, a partner at Flair Capital Partners, said in a statement. “They are building a platform that aligns with how clinical information is actually documented, and have already demonstrated the ability to turn it into meaningful, measurable outcomes. We believe this is a critical capability for organizations operating value-based care, and we’re excited to support the team as they scale.”
Keebler Health plans to use the funding to expand its team, continue commercial growth and support the infrastructure of value-based care organizations across the country. It will also support the company’s expansion into adjacent use cases such as compliance and audit workflows, including AI-powered RADV audit support.
“Discovering the real, unstructured clinical stories about these patients at scale is a core value driver for us in risk adjustment for these value-based care organizations,” Park said.
The company raised $1.8 million in a pre-seed funding round led by New Stack Ventures and $6 million in a seed round led by Freestyle Capital, Park told Fierce Healthcare.
Founded in 2023, the Durham, North Carolina-based company was founded by Park, Andrew Stickney, Dr. Kevin Hill, and founding chief medical officer Terrell Backus, who said the group “immediately” encountered a problem that led it to think about its clinical narrative.
“We’ve come to this real opportunity to discover unstructured clinical narratives and process them in a way that allows us to use software at scale to bring out the evidence we discover in these clinical areas,” Park said.
Park said one of the challenges with risk adjustment is the lack of external tools other than “traditional natural language processing tools,” which have since changed with the advent of LLM technology.
“Really, for the first time in history, we can use software at scale to read parts and understand unstructured clinical narratives,” Park says. “We built a tool that allows us to go back longitudinally through as much unstructured clinical data as we have available and really understand what’s going on in a patient’s narrative based on their notes, not necessarily just their claims.”
