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Fathom logo — AI-powered medical coding automation

Fathom

AI-powered medical coding automation

Founded 2017 United States San Francisco, United States 98 employees Series B Total: $60.86M AI, Financial Services +1

General Information

Company Name Fathom
Founded Year 2017
Location United States San Francisco, United States
Employees 98
Industries AI, Financial Services, Machine Learning
Funding Stage Series B
Social

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About Fathom

Fathom is an AI-powered medical coding automation startup founded in 2017 that aims to revolutionize healthcare systems globally. Its cutting-edge deep learning and NLP technologies enable autonomous medical coding with the highest automation rates and broadest specialty coverage, leading to reduced costs, increased accuracy, and rapid turnaround times. The company has garnered significant attention from prominent investors, including Lightspeed, Alkeon Capital, Google Ventures, 8VC, and Stanford, alongside endorsements from key health systems and executives like Cedars-Sinai and Jonathan Bush.

With its headquarters in the United States, Fathom recently secured a noteworthy $17.00M Series A investment on 20th September 2024, with participation from Active Capital, Y Combinator, Maven Ventures, Rackhouse Ventures, Telescope Partners, Zoom, and Character. The startup's innovative approach and strong financial backing position it as a promising player in the intersection of AI, financial services, and machine learning within the healthcare industry.

Business keywords: medical coding automation, autonomous medical coding, deep learning, NLP, revenue cycle management, software engineering, TensorFlow, big data, healthcare systems, real-time audits, business optimization

Services & Products

Medical coding automation
Revenue cycle management
Healthcare data analytics

Target Customers

Healthcare providers Healthcare organizations Healthcare revenue cycle operations

Funding Rounds & Investors (6)

View All
Funding Stage Amount Investors Lead Investors Date
Series B $46.00M 7
Founders Fund, Lightspeed Venture Partners +5
09 Nov 2022
Venture Round Undisclosed 1
Inflect Health
25 Apr 2022
Venture Round $50.00K 1
The Cedars-Sinai Accelerator
18 Feb 2021
Venture Round $14.81M 2
Winklevoss Capital, Tarsadia Investments
02 May 2019
Venture Round Undisclosed 1
XG Ventures
01 Jan 2018
Seed Round Undisclosed 1
CSC Upshot
01 Dec 2015

Fathom Alternatives & Competitors

View All Alternatives
Fathom vs
Emedlogix Inc.
Emedlogix Inc. United States

Next-Gen Computer Assisted Coding for Healthcare

11 employees
AI, Health Care
Fathom vs
AKASA
AKASA United States

AKASA is the leading provider of generative AI solutions for the healthcare revenue cycle.

Series C
223 employees
AI, Health Care
Fathom vs
Suki
Suki United States

Building presence at the heart of care.

Series D
398 employees
AI, Health Care

FAQ About Fathom

AI-powered medical coding automation
Fathom was founded in 2017.
Fathom is headquartered in San Francisco, United States.
Fathom operates in AI, Financial Services and Machine Learning. Its work centres on medical coding automation, autonomous medical coding, deep learning and NLP. Its customers include Healthcare providers, Healthcare organizations and Healthcare revenue cycle operations.
Fathom has approximately 98 employees.
Fathom has completed 6 funding rounds, raising a total of $60.86M. The latest funding stage is Series B.
Fathom offers: Medical coding automation, Revenue cycle management, Healthcare data analytics.
Top alternatives and competitors to Fathom include Emedlogix Inc., AKASA, Suki, Particular Audience, Pensa Systems. These companies operate in related industries and serve comparable markets. You can compare them side by side on Bounce Watch.
Fathom and Emedlogix Inc. are both companies in similar industries. Compare their funding, team size, growth signals, and market position on Bounce Watch to see which one fits your needs.

Source: BounceWatch company record for Fathom, https://bouncewatch.com/company/fathom, updated 30 July 2025. When citing, please name BounceWatch and link this page.

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