Heidi Company Spotlight: Building an AI Care Partner

Heidi began with one of healthcare's least glamorous problems: clinicians spending the evening finishing documentation after the patients had gone home. The Melbourne company now wants to become something larger than an ambient scribe. Heidi is building an AI Care Partner that supports clinical work from documentation and evidence retrieval to forms, coding, tasks, and connected workflows.

Founded in 2021 by Thomas Kelly, Waleed Mussa, and Yu Liu, Heidi sits at the intersection of a labor-capacity problem and a software-adoption problem. Healthcare systems need more clinical time, but every new tool must clear demanding tests around privacy, integration, accuracy, governance, and trust. That makes Heidi's progress worth watching. The product can spread quickly through individual clinicians, while the company must still earn its way into hospitals and health systems one workflow at a time.

About Heidi

Heidi is a private healthcare AI company headquartered in Melbourne, Australia. Thomas Kelly, a physician by training, serves as co-founder and CEO. Yu Liu is co-founder and CTO, while Waleed Mussa is co-founder and CFO, according to Heidi's current careers and media pages.

The founding logic came from clinical friction. During medical training, Kelly saw how administrative work pulled attention away from patients. Heidi's first wedge was ambient documentation: listen to a consultation, create a structured clinical note, and let the clinician review the output before it enters the record. That last step matters. Heidi explicitly says its software supports clinical judgment rather than replacing it.

The platform now includes Scribe, Evidence, Remote, Forms, Dictate, Tasks, medical coding, template tools, and EHR integrations. It serves individual clinicians, practices, hospitals, and health systems across primary care, specialties, emergency medicine, mental health, allied health, dentistry, veterinary care, and clinical training.

Why Heidi Matters Right Now

Ambient documentation has become a crowded category because the first-order value is easy to understand: less typing and more attention for the patient. The harder contest begins after the note. Health systems want software that fits existing records, supports governance, respects regional data rules, and can take on more administrative work without turning clinical care into an automation experiment.

Heidi's strategy is to use documentation as the doorway to that broader workflow layer. Evidence brings clinical guidance into the session. Forms and coding address work created after the encounter. Tasks, communication tools, and integrations connect the generated note to what happens next. The company is betting that the durable product will be the workflow around the conversation, not transcription alone.

The scale is already material. In its September 2026 announcement, Heidi reported supporting 2.8 million consultations each week, more than 175 million patient visits in total, and 67 million clinical hours returned. The company said clinicians use the platform in 190 countries and 110 languages. Heidi also reported annual recurring revenue rising from $1 million to $50 million in two years, reaching that mark in April 2026. These are company-reported figures, but they frame the transition from fast adoption to institutional execution.

From Clinician Adoption to Health-System Infrastructure

Heidi's named deployments and partnerships show where the company is trying to go. The company's media room points to work with Metro South Health and the Royal Children's Hospital in Australia, Halton Healthcare and North York General in Canada, and integrations involving QHR Technologies' Accuro EMR and Vim. Each relationship is different, but together they reveal the operating challenge: clinical AI must work inside local systems, not merely beside them.

Security and governance therefore belong in the product story. Heidi's official product information lists SOC 2 Type II, ISO 27001, and ISO 42001 certifications, along with regional privacy and data-residency commitments. Certifications do not settle questions of clinical safety or implementation quality, but they create a baseline for enterprise conversations. As Heidi moves into more tasks, the requirement for clinician review, transparent workflows, and measurable outcomes becomes more important, not less.

That is also why the company's September 2026 financing was split into two pools. A $100 million Series C led by Blackbird funds the company, while a separate $240 million investment from General Catalyst's Customer Value Fund is designed to support growth and customer adoption. The structure makes the real constraint visible. Building the product is expensive. Deploying it across large healthcare institutions is a different expensive job.

Leadership, Culture, and Hiring

Heidi's founders combine clinical, technical, and operating perspectives. The company has also added regional clinical and commercial leadership as it expands. In its Canada launch announcement, Heidi named Toronto its North American headquarters and appointed Dr. Sameer Shaikh as Clinical Director for Canada. The company said it had already hired 17 people there and expected to add 30 more roles across engineering, clinical, and commercial work.

The Heidi careers page reports more than 500 employees and eight offices across Australia, the United States, the United Kingdom, Canada, and Singapore. Its stated values emphasize long-term thinking, ownership, fast iteration, and learning from clinicians. The active roles span product, engineering, sales, customer success, clinical work, and regional expansion.

Hiring is not proof that a strategy will work. It is evidence of where the hard work is accumulating. Heidi needs builders who can improve the product, clinicians who can pressure-test it, and implementation teams who can navigate hospital systems. That mix says more about the next phase than a generic growth slogan ever could.

What Heidi Signals for Clinical AI

Heidi's expansion reflects a broader shift in clinical AI. The category is moving from a point solution that produces notes toward an operating layer that helps move information through care. That opens more value, but it also raises the standard. A system that touches evidence, coding, follow-up, and tasks must be judged by integration, governance, reliability, and the quality of the human decisions around it.

Heidi has assembled the capital, reach, and clinician adoption to compete for that role. The next proof will not come from another usage chart alone. It will come from repeatable health-system deployments that save time without weakening the human and clinical accountability at the center of care.