Dr. Jay Shah Joins Amigo AI
Dr. Jay Shah, MD, is the Chief of Medical Staff at Stanford Health Care in Palo Alto, California. He recently accepted the role of Chief Medical Advisor at Amigo AI — a fast-growing agentic AI startup reshaping how patients access care. His appointment marks a significant step for the company as it scales its clinical AI platform globally.
A 23-Year Clinical Career Backing a Bold Vision
Dr. Shah brings deep experience to this advisory role. Over 23 years, he practiced medicine at some of the country’s most respected institutions — Stanford, Columbia, and MD Anderson. That perspective now informs how Amigo trains its AI agents.
“In my 23 years of practicing medicine, I’ve watched the demand for care outpace our ability to deliver it,” said Dr. Shah. “Amigo’s approach of training agents with the same rigor we expect of clinicians means they can operate at the standard I’ve seen at Stanford, Columbia, and MD Anderson.”
What Is Amigo AI?
Amigo AI builds and deploys patient-facing clinical AI agents. These agents handle high-value healthcare workflows, including intake and triage, personalized care navigation, and round-the-clock patient support. The New York-based company partners with healthcare organizations worldwide to define their AI strategy and implement custom agents at scale.
How the Platform Works
Amigo’s platform connects multiple AI agents that work together — much like a human care team. Furthermore, each agent shares unified patient context in real time. This approach eliminates information loss during clinical handoffs. The system integrates directly with major electronic health record (EHR) platforms, including Epic, Oracle Health, and Athenahealth.
Additionally, the platform supports deployments in over 100 languages. It also maintains full compliance with HIPAA, SOC 2 Type II, and GDPR regulations.
Proven Real-World Results
The data tells a compelling story. In just six months, Amigo agents completed over three million patient encounters globally — with zero safety incidents. Current healthcare partners include Eucalyptus, Diverge Health, and The Care Clinic.
The Digital Residency Training Model
One defining feature sets Amigo apart from typical healthcare AI solutions: the “Digital Residency.” General-purpose large language models (LLMs) are prone to hallucinations and lack clinical guardrails. Consequently, deploying these models directly with patients creates serious liability risks. Amigo takes a fundamentally different approach.
Training AI Agents Like Doctors
“We train our agents like doctors because mistakes can cost lives in healthcare,” said Ali Khokhar, Founder and CEO of Amigo AI. “No agent should interact with a real patient until it has been rigorously trained and proven safe.”
Before any deployment, each agent completes millions of simulated clinical scenarios. These simulations reflect the specific patient population of the deploying organization. As a result, agents reach a 100% safety pass rate before they interact with real patients.
Why Simulation-First Safety Matters
Health systems that deploy generic AI chatbots risk exposing patients to inaccurate or harmful responses. By contrast, Amigo’s simulation-first model builds clinical trust through rigorous pre-deployment validation. Moreover, the architecture mirrors a human care team — agents collaborate in real time, drawing patient context directly from EHR integrations.
“Amigo is addressing one of the hardest problems in healthcare AI — deploying autonomous systems where trust and safety are non-negotiable,” said Sabrina Albert, Partner at Madrona. “Their simulation-first approach to clinical safety positions them to define the standard for patient-facing AI.”
Series A Funding Breakdown
On March 10, 2026, Amigo AI closed an $11 million Series A funding round. Madrona led the round, with Optum Ventures participating. Together with a seed round co-led by General Catalyst and GSV Ventures, the company has now raised a total of $17 million.
Strategic Use of Capital
Amigo plans to use the new funds to expand operations and accelerate product development. In addition, the company is deepening its clinical leadership bench — as evidenced by Dr. Shah’s appointment. The raise also aligns with a favorable regulatory environment. Policy shifts like the CMS ACCESS model are actively encouraging technology-enabled care delivery. Meanwhile, provider demand for clinically safe AI agents continues to rise.
Why This Matters for Healthcare
The global health worker shortage is a mounting crisis. Projections estimate a shortage of 11 million health workers worldwide by 2030. Clinical AI agents offer a credible path to bridging that gap — but only when built to meet clinical-grade standards.
Expanding Care Without Compromising Safety
Amigo’s model tackles this challenge head-on. Its platform expands the capacity of existing care teams while maintaining patient safety. Additionally, Dr. Shah’s credibility as a top clinician lends weight to the company’s claims around clinical-grade performance. His involvement signals that Amigo’s agents are not just technically capable — they are medically validated.
Together, the funding milestone and leadership appointment reflect a broader shift in healthcare AI: the move from passive AI tools to autonomous, patient-facing clinical agents that work continuously alongside care teams.
Key Takeaways
- Dr. Jay Shah, Chief of Medical Staff at Stanford Health Care, is now Chief Medical Advisor at Amigo AI.
- Amigo AI raised $11 million in a Series A on March 10, 2026, led by Madrona and Optum Ventures.
- Total funding now stands at $17 million, including a seed round from General Catalyst and GSV Ventures.
- The company’s Digital Residency model trains AI agents through millions of simulated clinical scenarios before deployment.
- Amigo agents have completed 3 million+ patient encounters globally with zero safety incidents.
- The platform integrates with Epic, Oracle Health, and Athenahealth, and supports over 100 languages.
