Heidi Health closed a $65 million Series B in October 2025 led by Point72 Private Investments, valuing the company at $465 million. This represents significant growth from the company's $100 million valuation in May 2025.

The company previously raised a $16.6 million Series A follow-on round in March 2025 with participation from existing investors including Blackbird Ventures, Headline, LocalGlobe, and Latitude. Other notable investors include Anthology (backed by Menlo Ventures and Anthropic), HESTA, Possible Ventures, Archangel Ventures, and January Capital.

Heidi originally launched as Oscer and raised a $5 million seed round in August 2021 backed by Blackbird Ventures. The company has raised approximately $86.6 million in total funding across all confirmed rounds.

Heidi Health is an AI-powered ambient scribe that automatically generates clinical documentation during patient consultations. The platform uses real-time audio transcription to listen to doctor-patient conversations and creates structured medical notes, referral letters, and patient handouts without requiring manual input.

During a consultation, Heidi's ambient microphone captures dialogue in over 110 languages and converts it into SOAP-style notes. Clinicians can insert voice commands like "Heidi, add diabetes foot check to plan" to modify documentation in real-time.

The platform includes several core modules: Ask Heidi functions as a ChatGPT-like interface for querying patient history and generating summaries, Context links previous sessions and uploaded documents for comprehensive patient records, and Templates & Coding allows specialty-specific note formats with automatic billing code suggestions.

Heidi operates across multiple access points including desktop and mobile apps, a Chrome extension, and a widget that integrates with browser-based electronic health records. The Magic Paste feature allows clinicians to drop completed notes directly into their existing EHR systems with one click.

The platform maintains a privacy-first architecture where audio is streamed but not stored, with all processing occurring on privately-hosted servers that comply with ISO 27001, SOC 2, HIPAA, GDPR, and NHS-DSP standards.

Heidi operates on a B2B SaaS model targeting individual clinicians and small to medium practices through a product-led growth strategy. The platform uses freemium pricing where users can access basic functionality at no cost before upgrading to paid subscription tiers.

The company's go-to-market approach focuses on bottom-up adoption where end-users, typically doctors, make purchasing decisions directly rather than requiring lengthy enterprise sales cycles. This allows Heidi to scale rapidly across diverse medical specialties and geographic markets.

Heidi's cost structure includes cloud infrastructure and AI model processing, with gross margins typical of data-heavy SaaS companies rather than pure software businesses. The platform's unit economics benefit from high utilization as more consultations per user drive better cost efficiency.

The business model creates natural expansion opportunities as practices increase their usage of automated documentation features. Users typically start with basic note-taking and expand to include pre-chart summaries, coding assistance, and patient communication tools.

Revenue scales through both user acquisition and increased consumption per user as clinicians integrate Heidi more deeply into their workflows. The platform's unlimited user model within practices encourages broad adoption while tying billing to actual usage rather than seat count.

Microsoft's Nuance DAX Copilot leverages deep Epic and MEDITECH integrations to serve over 150 U.S. health systems. The platform benefits from Microsoft's ability to bundle Azure licenses and Teams telehealth services, creating pricing leverage through comprehensive enterprise contracts.

3M Fluency Align brings established speech-to-text capabilities to over 300,000 clinicians while embedding AWS Bedrock and Comprehend Medical for enhanced AI functionality. Augmedix operates as a public company processing over 70,000 notes weekly through a hybrid model combining human quality assurance with Google MedLM technology.

AWS HealthScribe offers HIPAA-eligible APIs that enable EHR vendors and startups to embed Amazon's speech recognition and generative AI capabilities directly into their platforms. This infrastructure-as-a-service approach threatens to commoditize core note-generation functionality through usage-based pricing.

Google Cloud and Microsoft Azure provide similar foundational AI services that larger healthcare technology companies can leverage to build competing ambient documentation features. These platforms compete on the underlying technology stack rather than end-user applications.

Freed employs a similar bottom-up strategy targeting individual practitioners and has scaled to $13 million ARR through product-led growth tactics. The company focuses on the same small to medium practice segment that drives much of Heidi's adoption.

Abridge has secured significant venture funding and partnerships with major health systems, positioning itself as an enterprise-focused alternative to Heidi's SMB approach. Nabla and Ambience have achieved billion-dollar valuations by targeting different segments of the ambient AI scribe market.

Heidi is expanding beyond basic transcription to become a comprehensive AI care partner for clinicians. The 2025 roadmap includes pre-chart summaries, clinical guideline lookups, automated form filling, and patient outreach capabilities that capture more value from each patient encounter.

The platform's developer-friendly Epic in-workflow app and API integrations position Heidi as a foundation for third-party applications like triage chatbots and referral routing systems. Platform fees and marketplace revenue represent significant TAM expansion beyond core documentation.

Specialty-specific AI playbooks for oncology, psychiatry, and other medical fields allow Heidi to command premium pricing for higher-accuracy, specialized documentation that addresses niche clinical requirements.

Heidi's Series B funding supports dedicated sales teams in the U.S., UK, and Canada to target large hospital systems where over 70% of clinicians still rely on legacy dictation or manual documentation. Enterprise customers represent substantially larger contract values than the company's initial SMB focus.

The veterinary market presents a parallel expansion opportunity with over 150,000 clinics globally facing similar documentation challenges but with faster purchasing cycles. Heidi's deployment with Greencross demonstrates the platform's applicability beyond human healthcare.

Government and payer partnerships, including pilots with the Government of Yukon and NHS-affiliated trusts, open pathways to public-sector procurement where clinician time savings translate directly to cost reductions.

Heidi already operates in 116 countries with support for 110 languages, providing a foundation for deeper market penetration in EMEA and APAC regions. The company is establishing operational hubs in key markets to support local sales and customer success efforts.

Emerging adoption in France, Spain, Germany, South Africa, Singapore, and Hong Kong demonstrates organic international demand that can be accelerated through localized go-to-market strategies and region-specific compliance capabilities.

The global shortage of healthcare workers creates universal demand for productivity-enhancing tools like AI scribes, expanding Heidi's addressable market beyond English-speaking countries to any region with modern healthcare infrastructure.

EHR integration: While Heidi operates as a standalone solution, deeper EHR integration by incumbents like Epic and Oracle-Cerner could commoditize ambient documentation features and reduce demand for third-party solutions. Native EHR scribes bundled into existing contracts pose a significant competitive threat to independent vendors.

Regulatory scrutiny: Healthcare AI faces increasing oversight from bodies like the TGA in Australia and FDA in the United States, potentially requiring costly compliance processes or limiting product capabilities. Changes in medical liability standards for AI-generated documentation could impact adoption rates and increase operational complexity.

Margin compression: As cloud providers like AWS and Google offer ambient AI capabilities as infrastructure services, the underlying technology becomes commoditized and competition shifts toward price rather than features. Heidi's gross margins could face pressure as data processing costs remain significant while pricing power diminishes in an increasingly competitive market.