Revenue cycle · Autonomous medical coding AI
RapidClaims
RapidClaims is AI software that codes medical charts, flags documentation gaps and checks payer rules before claims go out, for physician groups, health centers and health systems.
Strong fit
- Multi-specialty physician groups with coding backlogs
- Community health centers that want to catch denials before claims go out
- Groups in value-based contracts that need risk adjustment coding
Weak fit
- Hospitals that need inpatient facility coding today
- Buyers who need a posted price
- Buyers who want a vendor with a long track record
Bottom line
RapidClaims is a reasonable choice for physician groups, health centers and specialty practices that want AI to code charts and catch denial risks before claims go out. It suits groups willing to run its side-by-side test on past charts. Buyers who want a long track record should weigh its 2023 start.
Score breakdown
Weights: Outcomes 35% · Product 30% · Implementation 20% · Pricing clarity 15%.
Dushyant Mishra, Jot Sarup Singh and Abhinay Vyas founded RapidClaims in 2023, and Mishra is chief executive. The company is based in New York. Mishra worked at Abbott, Singh built products at Postman, and Vyas led data science teams at Novartis.
Its coding agents read each clinical note, assign codes with an audit trail, and send hard cases to human coders. RapidClaims says it needs about 500 charts to tune its models for a new client, and that most AI vendors need 10,000 or more.
Its other tools flag documentation gaps for clinical documentation teams, capture risk adjustment (HCC) codes for value-based contracts, and check payer rules before a claim is built. RapidClaims also offers revenue cycle services that use its software.
RapidClaims says it is live in more than 25 specialties and codes with high accuracy without human review in more than 20 of them. Its customers include community health centers, physician groups and outpatient units of health systems.
Black Book ranked RapidClaims first in its 2026 study of AI claims automation, and Frost & Sullivan gave it a 2025 technology innovation award. It raised $11 million, including an $8 million Series A led by Accel in 2025.
CodaMetrix and Fathom fit health systems that want coding AI with a longer record at scale. Arintra fits groups that code inside Epic or athenahealth, XpertDox fits urgent care and primary care groups, and Nym fits buyers that want a coding engine for specific specialties.
Competitor landscape
| Vendor | Overall | Ease of implementation |
|---|---|---|
| CodaMetrix | 7.6 | 7.3 |
| Fathom | 7.5 | 7.2 |
| Arintra | 7.2 | 7.1 |
| RapidClaims | 7.1 | 7.5 |
| XpertDox | 7.0 | 7.0 |
| Nym | 6.6 | 6.4 |
Pricing
| Item | Detail |
|---|---|
| Model | RapidClaims prices its software by contract. It also sells revenue cycle services that use its software. |
| What usually drives cost | For RapidClaims, cost depends on chart volume, specialties, and which modules you add, such as documentation review, risk adjustment coding and denial work. |
| What to ask before you buy | Ask RapidClaims for its price per chart, the share of charts sent to human coders in your specialties, and the results of a test on your own past charts. |
| Note | RapidClaims offers to test its coding against your last six months of charts before you switch. |
| Published pricing | RapidClaims does not publish a price list. |
Methodology
| Weight | Factor | What it measures |
|---|---|---|
| 35% | Customer outcomes | Whether buyers get measurable operational or clinical-workflow results after go-live |
| 30% | Product | Capability depth, reliability, and fit for the job the category buys |
| 20% | Implementation | How hard it is to stand up, integrate, train, and stabilize |
| 15% | Pricing clarity | Whether a buyer can model total cost without a mystery quote |
| Label | Meaning |
|---|---|
| Highly recommend | Strong outcomes and product with manageable caveats |
| Recommend | Solid fit for the right buyer; know the tradeoffs |
| Conditional | Only with a specific use case or heavy caveats |
| Not recommended | Avoid for most buyers in this category |
Read our full methodology for how we weight scores and assign recommend labels.