Baba’s $40 Million Bet on Medicare Navigation Signals Growing Demand for AI Care Coordination
Applied artificial intelligence company Baba has raised $40 million in series A funding to expand a care platform aimed at Medicare and Medicaid patients who often face the most fragmented parts of the U.S. health system. FirstMark Capital led the round, with participation from CVS Health Ventures and Valtruis. Returning investors General Catalyst, Genius Ventures and Ground Up Ventures also joined the financing.
Baba’s pitch is straightforward and ambitious at once: use AI to reduce the friction that surrounds government-sponsored coverage, from care coordination to paperwork, billing and insurer calls. For older adults and people with more complex needs, those administrative bottlenecks can become a clinical problem in their own right. Missed appointments, delayed referrals and unanswered coverage questions do not stay administrative for long; they show up as lost time, untreated symptoms and avoidable family stress.
A Platform Built Around Government-Sponsored Coverage
Founded in 2025, Baba connects Medicare and Medicaid patients to dedicated care teams that include care coordinators and licensed therapists. The company says it has partnered with national health plans, government agencies and other organizations while supporting more than 10,000 patients. It also says 100,000 families are on its waiting list, a sign of demand that outpaces current capacity.
The platform is aimed at a population that is often older, rural and medically complicated, which matters because these patients are more likely to need repeated navigation across primary care, specialty care, behavioral health and benefits administration. In that setting, a care platform is not just a convenience layer. It becomes part of the infrastructure that helps determine whether patients can actually use the care they are entitled to receive.
FirstMark Capital co-founder and partner Rick Heitzmann framed the deal as part of a broader consumerization of healthcare, but the clinical stakes are more specific than that language suggests. Medicare and Medicaid patients frequently encounter competing instructions from payers, providers and pharmacies. An AI-supported coordination model is designed to reduce those collisions, particularly when families are trying to manage chronic illness over long periods of time.
Value-Based Care Is the Commercial Endgame
CEO and founder Connor Sweeney said the new capital will help Baba scale how care is delivered and coordinated for people on government-sponsored coverage. He also pointed to a deeper focus on payer relationships and value-based arrangements, with the company working toward a model in which it takes on risk.
That business model is important because the economics of navigation and coordination become more durable when they are tied to outcomes and accountability rather than one-off transactions. In value-based care, the pressure shifts toward preventing avoidable deterioration, reducing unnecessary utilization and keeping patients engaged with the right services at the right time. For a platform built around Medicare and Medicaid populations, that creates a direct commercial link between operational efficiency and clinical reliability.
One sentence captures the core problem. Government-sponsored coverage often leaves patients with benefits on paper and confusion in practice.
The company’s focus on risk-bearing arrangements suggests it wants to move beyond being a support layer and into a more embedded role in care delivery. If that strategy works, it could make navigation services feel less like a customer service add-on and more like a clinically relevant extension of the care team. The challenge is execution, because the population Baba serves often has high acuity, multiple chronic conditions and social barriers that are difficult to solve with software alone.
CMS Selection Adds Regulatory Credibility
The U.S. Centers for Medicare and Medicaid Services selected Baba for the 10-year ACCESS model, a detail that gives the company regulatory visibility as it expands. Public-sector alignment matters in this part of healthcare because Medicare and Medicaid workflows are shaped by federal and state policy, plan design and quality measurement. A company operating here has to build for administrative complexity from the start.
CMS involvement also suggests that Baba’s model fits with a broader policy interest in care coordination and cross-payer alignment. For a company using AI to help patients with long-horizon needs, policy recognition can function as a practical gateway to scale. Health plans and public programs tend to move cautiously, but selection for a federal model can reduce uncertainty around whether a platform belongs in the mainstream of care delivery.
The company has now paired that policy validation with venture backing from investors tied to healthcare, consumer platforms and payer strategy. CVS Health Ventures brings a payer-and-retail perspective that may help Baba refine how its services fit into existing coverage workflows, while General Catalyst and the other returning backers suggest early investors are still aligned with the company’s direction.
Applied AI Goes Beyond Scheduling and Reminders
Baba is also building an applied research effort focused on AI solutions for complex care. Its BabaBench benchmark measures frontier AI agents on long-horizon patient advocacy tasks, including paperwork, billing and insurer calls. Those may sound like back-office chores, but they are often the exact tasks that determine whether patients can access treatment on time.
By testing how AI handles these real-world friction points, the company is placing technical performance closer to the actual burdens patients face. A model that can help manage a billing dispute or navigate prior authorization is addressing a failure point in the care continuum, not just a convenience feature. The benchmark approach also signals that Baba sees itself as more than a service company; it wants to shape how AI performs in medically consequential administrative work.
The central question is no longer whether AI can generate answers. It is whether AI can sustain reliable support across the long, messy, highly human process of getting care authorized, delivered and followed through.
For now, Baba has raised a sizable round, secured a federal model role and expanded its investor base. What remains to be proven is whether AI-driven navigation can consistently reduce the burden of Medicare and Medicaid complexity at scale, and whether those gains can translate into durable value-based contracts without losing the personal accountability that older and medically complex patients need.