Health Tech Startup Tennr Raises $101M to Fix Broken Patient Referrals

Tennr just closed a $101 million Series C funding round to tackle one of healthcare's most persistent problems. The New York-based startup uses AI to streamline the notoriously broken patient referral process that leaves more than half of Americans without the specialty care they need.

IVP led the round with participation from Google Ventures, Iconiq, Andreessen Horowitz, and Lightspeed. The funding values Tennr at $605 million, less than a year after its $37 million Series B.

The company was born from founder Diego Baugh's frustrating personal experience. After being hospitalized with stomach issues in college, he waited six weeks to hear from a specialist, skipped the appointment, and ended up hospitalized again. Another six-week wait followed before the specialist finally reached out.

That nightmare scenario plays out millions of times across American healthcare. While one-third of Americans get referred for specialty care each year, more than half never make it to their next appointment. The referral system is tangled in bureaucracy, paperwork delays, and communication breakdowns between primary care doctors and specialists.

Tennr built a specialized AI model trained on tens of millions of medical documents to automate the referral workflow. The platform handles everything from parsing illegible doctor's notes to verifying insurance eligibility and payer rules. CEO Trey Holterman, who previously worked at Strava and Medicare platform Health IQ, believes their focused approach beats general AI models for this specific use case.

"It's not about automating work," Holterman said. "It's really about making sure that the patient actually gets the service and understands what it's going to cost, so that they show up."

The company has tripled revenue since October, now generating eight figures annually. That growth caught the attention of IVP partner Zeya Yang, who originally invested in Tennr's Series A while at Andreessen Horowitz and decided to lead the Series C after joining IVP.

Yang sees massive expansion potential beyond the core referral problem. Tennr can build additional tools for specialists and primary care physicians while creating new revenue streams around insurance verification and patient communication. The company is already developing network features that give both doctors and patients visibility into the referral and payment process.

The timing reflects broader trends in healthcare technology, where AI companies are racing to solve operational inefficiencies. But Holterman deliberately avoids positioning Tennr as just another AI healthcare startup, preferring to focus on practical problem-solving over flashy technology.

Tennr's specialized model gives it advantages over general AI platforms that lack the hyper-specific medical training data. The company's approach to interpreting complex medical documents and understanding healthcare workflows creates defensible differentiation in a crowded market.

The funding positions Tennr to expand into new medical specialties and build out additional workflow tools. With healthcare costs continuing to rise and patient satisfaction remaining low, fixing the referral bottleneck could unlock significant value for the entire system while improving outcomes for millions of Americans stuck in bureaucratic limbo.