AI Is Becoming the Front Door to Complex Care

Venture-backed digital health platforms are no longer positioning AI as an assistive tool within existing care models. Increasingly, they’re building entire care infrastructures around it. Two newly funded startups, like Citizen Health and Isaac Health, are taking different but complementary approaches to this shift, using AI to reengineer access, navigation, and outcomes for historically underserved populations. Together, their strategies signal a broader industry recalibration: AI is becoming the care journey.

While Citizen Health focuses on rare disease and complex chronic illness, and Isaac Health targets dementia and brain health, both ventures raise the same strategic question for health systems, payers, and regulators: what happens when AI platforms not only augment clinical workflows but begin to define the standard of care?

Agentic AI and the Rise of Proactive Navigation

Citizen Health’s vision centers on “agentic AI,” technology that doesn’t just interpret health data but actively guides patients to the next best step. With $30 million in Series A funding from investors including 8VC and Headline, the company is building a personalized AI Advocate for patients with rare and complex diseases. Unlike traditional digital health tools that wait for user input or physician referral, Citizen’s model is designed to anticipate needs, recommend actions, and connect patients with community-based and clinical resources in real time.

By fusing AI, patient-reported data, and peer communities, Citizen is crafting a platform that reframes care from reactive treatment to proactive orchestration. That distinction matters. Nearly 70% of its patient advocacy group partners joined organically—a signal that users aren’t being driven by marketing, but by value. And with the FDA already accepting Citizen’s patient-contributed data for regulatory submissions, the platform’s credibility is extending beyond patient empowerment into drug development and clinical research.

This trajectory aligns with broader signals from federal agencies. The FDA’s 2024 innovation roadmap emphasized the need for advanced data models and patient-centered design in rare disease care. Meanwhile, shifting NIH funding priorities are pushing research networks to partner with more nimble, data-rich platforms like Citizen. In this context, agentic AI is a necessary mechanism for addressing systemic fragmentation.

Scaling Specialist Access with AI-First Infrastructure

Isaac Health is taking a parallel but distinct approach: using AI to deliver specialist-level dementia care at national scale. With $10.5 million in Series A funding led by Flare Capital Partners, the company has rolled out a virtual brain health platform that’s now live in all 50 states. Its model combines patented AI-based screening with virtual neurology consults, predictive analytics, and proactive care management.

The goal is to compress the 36-month average wait time for cognitive care down to days, and to shift diagnosis and treatment upstream. In early results, 92% of Isaac’s patients saw improvement in cognitive goals within three weeks, with 73% showing gains in neurocognitive function over six months. This isn’t just a UX upgrade. It’s a redefinition of what dementia care can look like when specialist workflows are reengineered around scalable AI rather than brick-and-mortar bottlenecks.

The platform’s value proposition resonates strongly with public health imperatives. Dementia is projected to affect over 12 million Americans by 2035, but fewer than 10% receive timely specialist input. Traditional care pathways rely on siloed referrals, constrained capacity, and episodic interventions. Isaac Health’s model eliminates those constraints, offering a continuous, data-driven, and clinically validated alternative. This aligns with CMS’s increasing focus on home-based and value-based models for cognitive care, as highlighted in its recent Alzheimer’s & Dementia Care Initiative.

Toward a New Category of Digital Front Doors

Together, Citizen Health and Isaac Health expose a deeper pattern: a shift from tools that support existing care infrastructure to platforms that are the infrastructure. This represents a material departure from early digital health models that focused on engagement, monitoring, or administrative automation. Instead, these companies are making AI the entry point for clinical care—especially in conditions marked by diagnostic ambiguity, long referral chains, and unmet patient needs.

For payers and health systems, this introduces both opportunity and friction. On one hand, AI-first platforms offer a solution to specialist shortages, rising costs, and fragmented access. On the other, they challenge traditional notions of gatekeeping, reimbursement, and clinical authority. If a patient’s first and most trusted interaction is with a virtual advocate—not a provider—then oversight, interoperability, and care coordination must evolve accordingly.

Moreover, these models place new demands on data governance. Citizen Health reports that 98.3% of patients voluntarily contribute data for research—a rate that far exceeds typical consent models. This suggests that trust in AI-enabled platforms may be higher than anticipated, especially when transparency, design, and advocacy are front-loaded. Yet this also raises regulatory questions about data ownership, secondary use, and integration into FDA or CMS-aligned workflows. As AI becomes the touchpoint for diagnosis and navigation, federal agencies will need clearer frameworks for validation, accountability, and patient safety.

Redesigning Around the Margins Is Redesigning the Core

Rare disease and dementia care have long lived at the margins of system design, underfunded, understudied, and underserved. What’s emerging now is not just an innovation cycle but a category shift. Companies like Citizen and Isaac are treating these complex, overlooked populations not as edge cases, but as the proving grounds for entirely new models of care.

The implications ripple outward. If AI can safely and effectively guide a rare disease patient through a clinical trial or deliver timely cognitive care across all 50 states, then why not apply the same infrastructure to oncology, cardiology, or maternal health? The systems being piloted at the margins today may well become the templates for broader transformation.

For stakeholders tasked with integrating, regulating, or funding these models, the message is clear: this is not about digital enhancement. It’s about infrastructure replacement. The next era of care delivery will not be AI-supported. It will be AI-initiated. The organizations that recognize this early will have a strategic advantage. The ones that resist may find themselves navigating from behind.