Hiro is an AI-powered platform designed for healthcare revenue cycle management (RCM). The company applies Machine learning models to automate and optimize administrative processes such as medical coding, claim submission, and denial management. Its primary goal is to reduce the financial burden on healthcare providers by improving billing accuracy and accelerating payment cycles.
The platform integrates with existing electronic health record (EHR) and practice management systems, allowing providers to deploy it without overhauling their current infrastructure. Hiro's technology focuses on identifying patterns in claims data to predict and prevent denials before submission, as well as to streamline the resubmission process for rejected claims.
History and Funding
Hiro was founded in 2021 by a team with backgrounds in healthcare technology and Artificial intelligence research. The company is headquartered in San Francisco, California. In its early years, Hiro raised a seed round of $5 million in 2022, led by a healthcare-focused venture capital firm. A subsequent Series A round in 2023 brought in $18 million, with participation from investors specializing in enterprise software. As of 2024, the company has not disclosed its total valuation.
The founding team includes CEO Sarah Chen, who previously led product development at a major EHR vendor, and CTO Michael Rodriguez, a former machine-learning engineer at a large cloud provider. Their combined experience informed the initial design of Hiro's core algorithms, which were tested with a small group of beta clients in 2022 before broader commercial release.
Core Technology
Hiro's platform relies on Deep learning models, particularly Transformer (architecture)-based architectures, to process unstructured clinical documentation and convert it into accurate billing codes. The system uses Natural language processing techniques to extract relevant diagnoses and procedures from physician notes, reducing the manual effort required by medical coders.
The platform also employs predictive analytics to flag claims that are likely to be denied based on historical payer behavior. By analyzing thousands of data points - including payer-specific rules, patient demographics, and procedure types - Hiro's models can recommend corrective actions before submission. This approach has been shown to reduce denial rates by an average of 30% across its client base, according to company-reported metrics.
Product Offerings
Hiro offers several modules within its platform, each targeting a specific aspect of the revenue cycle:
- Coding Automation: Automatically generates ICD-10 and CPT codes from clinical notes, with a claimed accuracy rate of 95%.
- Claims Management: Submits claims electronically to payers and tracks their status in real time.
- Denial Workflow: Prioritizes denied claims based on likelihood of successful appeal and drafts appeal letters using Generative AI models.
- Payment Posting: Reconciles incoming payments with outstanding balances, reducing manual data entry errors.
These modules can be purchased individually or as a bundled suite. As of 2024, Hiro reports that its platform processes over 2 million claims per month for its clients, which include regional hospital systems and large physician groups.
Market Position and Competition
The healthcare RCM software market is competitive, with established players like Epic and Cerner offering integrated solutions. Hiro differentiates itself by focusing exclusively on AI-driven automation rather than serving as a full EHR system. This allows it to partner with providers using different EHRs, including those from Oracle Cloud Infrastructure and Amazon Web Services infrastructure.
Compared to other AI-focused RCM startups, Hiro emphasizes its transparent pricing model - clients pay a per-claim fee rather than a percentage of collected revenue. This structure has appealed to smaller practices that may be wary of contingency-based fees. The company has also published case studies with two named clients: a 200-bed community hospital in Ohio and a multi-specialty clinic in Texas, both reporting significant reductions in days-to-payment.
Future Directions
Hiro plans to expand its platform to include prior authorization support, a frequent source of administrative burden for providers. The company is also investing in Large language model capabilities to improve patient communication regarding billing, potentially offering chatbots that can answer payment-related questions. As of 2025, these features are in beta testing with select clients.
The company faces challenges related to data privacy and regulatory compliance, particularly around HIPAA. Hiro states that its infrastructure is HIPAA-compliant and that all models are trained on de-identified data. However, the broader adoption of AI in healthcare billing remains subject to evolving state and federal regulations, which could affect Hiro's growth trajectory.
See Also
References
Company press releases and public funding announcements from 2021-2024.