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AI account scoring and sales training for field sales reps · USA

Fathom AI: Revenue, team and how it was built

Small teamB2BSales

Fathom AI (AI account scoring and sales training for field sales reps, USA): About US$300K annual recurring revenue, April 2026. Evidence grade B: confirmed by two or more independent reports. Team: 3 founders working as partners, plus 12 AI agents, no employees reported (April 2026). Launched January 2026; still running.Added 5 November 2026 · updated 6 November 2026

Outcome
About US$300K annual recurring revenue, April 2026
Evidence
B confirmed by two or more independent reports
Launch
January 2026
Status
Still running
Team
3 founders working as partners, plus 12 AI agents, no employees reported (April 2026)
Outside funding
None; US$300 of starting capital, a venture term sheet declined
Main channel
Cold outreach

Fathom AI is a sales enablement platform from Austin, Texas. Sales enablement means software that gives sales reps the information and training they need before they meet a buyer. Fathom started with field reps who sell aesthetic devices and fillers to plastic surgeons, dermatologists and medical spas. Its core is account scoring: a model ranks every practice in a rep's territory by how likely it is to buy, so the rep visits the best prospects first. The company's site says that it builds these practice profiles from public sources and website scraping, and Fortune describes the role-play training in which an AI plays the buyer and corrects the rep.

Ben Hooten, the founder and CEO, was a medical device sales rep and a former U.S. Army computer intelligence specialist. The company's about page says that he used his own tool to close US$440,000 of device sales in one day before Fathom sold it to anyone. Sam Brown, the president, joined after he lost a job to an AI-related layoff, and Dan Crump, a former Marine with decades in technology sales, is the chief revenue officer. Fortune reported on 18 April 2026 that Fathom reached an estimated US$300,000 in annual recurring revenue within 12 weeks of an early-2026 launch, with gross margins above 90%, according to records Fortune reviewed. Annual recurring revenue (ARR) is the current yearly value of the subscription contracts. The company says it was founded in November 2025 and started with US$300.

This page grades every number by its evidence. The headline figure is grade B: a journalist reviewed the company's records, but no payment processor or filing confirms it, and it is the only dated revenue figure found. Most other numbers come from the company's own site. The page also shows four failed sales intelligence startups and two issues a reader should know: a customer's rep talked to the AI support agent and believed it was the CEO, and most testimonials on the site name a job title, not a person.

Fathom AI: About US$300K annual recurring revenue, April 2026. AI account scoring and sales training for field sales reps, USA, team of 2 to 10, evidence grade B.
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01

How much revenue does Fathom AI make?

Each row shows the evidence grade and the source numbers from the list at the end of this page. The grades are explained in How Aiolum verifies.

An estimated US$300,000 in annual recurring revenue 12 weeks after launch, with 3 partners and no outside money, from records that Fortune reviewed
FactValueGradeHow we knowSources
Annual recurring revenue, April 2026about US$300,000 (estimated)BFortune, 18 April 2026: an estimated ARR of US$300,000 within 12 weeks of launch, according to records reviewed by Fortune. Brown said in the interview: we launched 2.5 months ago, and right now, we have US$300,000 in ARR.[1]
Monthly equivalent of the ARRabout US$25,000 a monthcalcCalculated: 300,000 divided by 12 equals 25,000.[1]
Gross margin, April 2026above 90%BFortune, from the same records. Operating costs under 10% of revenue. The company's press page repeats both figures.[1, 4]
Capital used to start the companyUS$300BFortune: the total capital invested to start the company was US$300.[1]
Outside fundingnoneBFortune: no outside funding; the founders reached a term sheet with a venture investor and walked away. The press page says zero outside capital.[1, 4]
Team, April 20263 founders and 12 AI agentsBFortune calls it a three-person company structured as a partnership that distributes profits. The press page says 3 founders and 12 AI agents in production.[1, 4]
FoundedNovember 2025CCompany home page: Founded November 2025. The press page says 2025.[2, 4]
Launchearly 2026, probably JanuarycalcCalculated: Fortune says the company launched in early 2026 and Brown said it launched 2.5 months before the interview. The interview transcript linked in the Fortune article is dated 1 April 2026 in its file name; 1 April minus 2.5 months is mid-January 2026. The file itself could not be opened.[1]
Time from launch to the ARR figure3 monthscalcCalculated: January 2026 to April 2026. Fortune says within 12 weeks.[1]
Profitabilitycash-flow positiveBCrump told Fortune: we got paid today, as a matter of fact. We're cash-flow positive. The home page says profitable from month one (grade C).[1, 2]
ARR target for the end of 2026US$5 million across 15 to 18 enterprise customersCA projection the company gave Fortune, not a result. No later revenue figure was found.[1]
Customers live, late 20265, in four verticalsCHome page. The customers named on the site are Tiger Aesthetics, AVAVA, Sutter Medical Technologies USA, WhiteWater Midstream and Sekisui House USA.[2]
First customer result, Q1 2026225 net new accounts in one quarterBKirk Gunhus, who consults for Tiger Aesthetics, told Fortune that Tiger opened 225 net new accounts within one quarter of deploying Fathom, after none in 2024. He is also listed as an advisor on Fathom's about page.[1, 3, 6]
Pilot size at the first customer6 reps, each paying individuallyBGunhus told Fortune that the company could not afford the subscription, so six reps paid for it themselves.[1, 6]
Practices profiledmore than 35,000CTechnology page: 35K+ practices profiled, 15M+ data points. The home page counter showed 32,936 accounts scored as of 9 September.[9, 2]
Mobile appiOS and Android, April 2026CCEO's blog post of 23 April 2026 announcing the app.[7]

How to read this table: a grade B value was reported by Fortune from records it reviewed, or by another independent party. A grade C value is a statement by the company or its founders, on its site or in interviews. A "calc" value was computed on this page from the rows above it.

Fathom AI pricing in November 2026, from the company's pricing page (grade C). The company publishes no prices.
PlanPer month, billed yearly (US$)Per month, billed monthly (US$)Limit
Prospector (scored territory, mobile app, Echo phone agent)quotequoteper engagement
Sales Operating System (Prospector plus briefs and Coach role-play)quotequoteper engagement
Business Operating System (CRM replacement with AI agents)quotequoteper engagement

Every engagement is quoted on request. The price depends on the number of reps and seats, the products deployed, the territory, the integrations (Salesforce, HubSpot, QuickBooks, Microsoft 365) and whether a model is trained on the customer's own sales history. A typical pilot is a dozen seats for one quarter. Fortune reported that six reps at the first customer paid for the tool individually during the pilot.

02

When did Fathom AI launch, and how did it grow?

From a sales rep's own territory tool to an estimated US$300,000 ARR in about three months. Each entry carries its grade.

  1. Before 2025CBen Hooten, a medical device sales rep, builds a prospecting tool for his own territory. The company says he used it to plan a demo event in El Paso, Texas, and closed US$440,000 of device sales in one day. [3]
  2. 2025BAt a meeting, Kirk Gunhus, a long-time medical aesthetics sales leader, complains that no sales tool tells a rep which accounts in a zip code to visit. Hooten calls him the next weekend with a plan. [1]
  3. November 2025CFathom AI is founded in Austin, Texas, by Hooten, Sam Brown and Dan Crump, with US$300 of capital. [1, 2]
  4. Early 2026BLaunch. Tiger Aesthetics becomes the first customer, starting with a pilot of six reps who pay individually, then a national rollout. [1, 11]
  5. Q1 2026BTiger Aesthetics opens 225 net new accounts in one quarter, according to Gunhus. [1, 6]
  6. 2 April 2026CA Stanford Digital Economy Lab report describes, without naming it, a healthcare AI company that built territory intelligence for cash-pay medical aesthetics. Fathom's press page says this case is Fathom. [8, 4]
  7. 18 April 2026BFortune reports an estimated US$300,000 ARR within 12 weeks, gross margins above 90%, three partners, 12 AI agents and no outside funding. [1]
  8. 22 to 23 April 2026CFathom names two product lines, a Sales Operating System and a Business Operating System, and releases its iOS and Android app. [12, 7]
  9. Late 2026CThe site lists five customers in medical devices, ENT and surgical devices, energy and real estate, and a pricing page with quotes only. [2, 5]
03

Why did Fathom AI work?

Four causes, in the order they mattered. Each one is a reusable lesson.

01

A niche with no data to buy

Sales teams in insured healthcare buy claims data that shows which doctors do which procedures. Medical aesthetics is paid in cash by patients, so that data does not exist. The Stanford report that Fathom says describes it calls territory intelligence for this market not expensive or slow, but impossible. Fathom builds the profiles itself from public sources and practice websites.

02

Built by a rep for reps

Hooten used the tool in his own territory before selling it. The first customer came from a conversation with an industry contact, and the first pilot reps paid out of their own pockets because, as Gunhus told Fortune, it was making them money. The founders' sales careers were the distribution channel.

03

AI agents in place of staff

The company says 12 AI agents hold roles such as customer success, competitive research, email triage and collections. One agent checks the competition every two hours and files a briefing. This is why the founders told Fortune they did not need the engineering and customer success teams that a venture investor expected them to hire.

04

Few large contracts, quoted per customer

Fathom sells custom engagements to device makers and other companies with field sales forces, not self-serve subscriptions. A handful of contracts was enough for the estimated US$300,000 ARR that Fortune reported, and each new customer gets a scoring model tuned to its own products.

How it was built

These details come from the company's own pages and from Fortune. They are grade B and C. The company does not name its model provider. [1, 7, 9, 5]

  • Discovery: the mobile app runs live Google Places searches for practices of a given specialty in a city, then scrapes each practice website for device and treatment signals, then scores every practice with AI.
  • Two scores per account, Readiness and Opportunity, from a model tuned to each customer's product line, for example the filler and implant brands that Tiger Aesthetics sells.
  • Generated output: a product-specific sales brief exported as a PDF, a cold call script and an email for each practice, with local search volumes from Google data.
  • Coach: voice role-play in which the AI plays the practice, followed by scoring on seven skills.
  • Echo, a phone agent that briefs reps and turns voice memos into CRM notes. Fortune reports that a customer's rep was walked through a support issue by the AI and believed he was talking to Hooten.
  • Web app in TypeScript with server-side rendering, a separate database per customer with row-level security, each agent in its own container, and a dark Mapbox territory map in the mobile app.
  • Integrations with Salesforce, HubSpot, QuickBooks and Microsoft 365, quoted as part of each engagement.

Tools named in the sources

Each one opens its page in the Tools tab, with every story that uses it.

04

Who tried this before Fathom AI, and why did they fail?

Four companies in our database of failed startups sold sales intelligence or lead scoring to sales teams and failed. The values below are from that database and are not independently verified.

Died 2016 to 2019Burned US$120K

Index

The promise

Sales intelligence and analytics that pull scattered data together so sales teams see their best opportunities.

Why it died

Salesforce already sat inside its customers' systems, and Index could not show a clear return quickly enough to justify a switch. Cheaper niche tools undercut it.

Competition
Died 2016 to 2019Burned US$500K

Elucify

The promise

Accurate, current contact data for sales teams from a crowdsourced database.

Why it died

ZoomInfo and Clearbit had larger and more reliable databases. The crowdsourced data was hard to keep accurate, and users would not pay for data they could not trust.

Competition
Died 2017 to 2020Burned US$1.2M

Slik

The promise

A platform that analyzes large amounts of data to find and rank leads for sales teams.

Why it died

LinkedIn Sales Navigator and ZoomInfo offered similar features with broader data. Slik could not keep its data fresh, customers left, and it could not raise another round.

Competition
Died 2021 to 2024Burned US$15M

Toplyne

The promise

AI that predicts which free users of a software product will pay, and sends them to the sales team.

Why it died

When software companies cut their sales teams in 2022 and 2023, a lead scoring contract of tens of thousands of dollars a year competed with headcount for budget and lost.

No Market Need

The failed startups come from our database of 1,749 dead startups, retold here in our own words. Its entries are AI-assisted summaries of public sources, so these cards carry no evidence grade.

What changed

The failed companies sold general sales data to every industry and lost to ZoomInfo, LinkedIn and Salesforce, which had more data and were already inside their customers' systems. Elucify and Slik both failed partly because they could not keep their data fresh at an affordable cost.

Fathom chose one industry where the big data vendors have little, because cash-pay aesthetics produces no claims data. Language models made it cheap to read thousands of practice websites, extract the devices and services each one offers, and write a brief per practice, work that used to need research staff. AI agents also take over support and research, so three partners can serve national sales forces. Fortune reported that these choices let the company run at gross margins above 90% with no outside money.

05

Can one person copy Fathom AI now?

Not alone, and not without industry contacts. The pattern, yes.

Fathom's first customers came from the founders' own careers in device and technology sales, and the product is sold in custom contracts that need a person who knows the buyers. A solo founder without those contacts would struggle to repeat the first sales. The technical parts, scraping public business data, scoring it with a model and generating briefs, are within reach of one developer.

Where it is still open: The same method fits other industries where reps sell to many small businesses with no central data: dental equipment, veterinary clinics, salons, restaurant suppliers, building trades. Fathom itself says it is moving into dental and real estate.

  1. 1Pick an industry you have sold into yourself, where the usual data vendors have no good data.
  2. 2Build the tool for your own territory or job first, and measure the result in sales you closed.
  3. 3Sell a small paid pilot against a baseline, so the customer can see the difference in numbers.
  4. 4Use AI agents for support, research and email before hiring staff, and disclose to customers when they talk to an agent.

What could go wrong for Fathom AI?

The risks are the mirror image of the causes above.

One dated revenue figure

The US$300,000 ARR is an estimate that Fortune reported on 18 April 2026 from records it reviewed. It is the only dated revenue figure found. The US$5 million year-end target is a projection, and no later figure, payment-processor profile or filing was found. A reader could look for a later interview or a customer contract disclosure.

An AI agent taken for the CEO

Gunhus told Fortune that a Tiger Aesthetics rep called with a support issue, was walked through the solution by what the rep believed was Hooten on the line, and had no idea it was an AI. The article does not say whether the agent stated that it was an AI. The company's pricing page says its named agents never send without review, which concerns email, not phone calls.

Testimonials named by job title

Most quotes on the home page and customer pages give a job title and a company, such as Chief Insights Officer, Sekisui House, without a person's name. One quote names a sales training manager at Tiger Aesthetics. The site lists Fortune and the Stanford Digital Economy Lab under As seen in; the Stanford report does not name Fathom.

A customer source who is also an advisor

Kirk Gunhus, the industry consultant who gave Fortune the 225-account result, is listed on Fathom's about page as its advisor for commercial strategy. Fortune describes him as a consultant to Tiger Aesthetics and does not mention an advisor role.

Numbers that do not agree

Fortune and the Tiger customer page say Tiger opened no net new accounts in the year before Fathom. The home page says fewer than 40 in the prior year. The company's own blog calls 225 accounts in a quarter fifteen a month, but 225 divided by 3 is 75 a month.

Medical aesthetics and scraped data

Fathom sells to device makers in medical aesthetics, a market of cosmetic procedures. It is a business-to-business sales tool and makes no health claims to patients. Its practice profiles come from public sources and website scraping of businesses, including the names and credentials of decision makers that the Coach module shows.

Sources

The grade next to each source is the best grade that the source can support. "Read in full" means that the text of the page was downloaded and the numbers were checked in it.

  1. B Fortune, 18 April 2026, by Nick Lichtenberg: Meet the AI founders using agents to build instantly profitable 3-person companies
    Read in full. The ARR, margin, capital and funding figures are from records Fortune reviewed. Source for the founders, the first customer and the AI support agent anecdote. The transcript and numbers files it links could not be opened (403).
  2. C Fathom AI home page
    Read in full, 5 November 2026. Source for the founding month, the customer count, the products and the testimonials.
  3. C Fathom AI about page
    Read in full. Source for the founders' backgrounds, the US$440,000 single-day close and the advisors.
  4. C Fathom AI press page
    Read in full. Source for the team of 3 founders and 12 agents, the margin claims and the link to the Stanford report.
  5. C Fathom AI pricing page
    Read in full. No published prices; source for the product tiers and how quotes are scoped.
  6. C Fathom AI blog, 26 August 2026, by Ben Hooten: From Zero to 225 Net New Accounts in One Quarter
    Read in full. The company's account of the first customer result.
  7. C Fathom AI blog, 23 April 2026, by Ben Hooten: Fathom Is Now in Your Pocket
    Read in full. Source for how discovery, scoring, briefs and Coach work, and for Google Places and Mapbox.
  8. C Stanford Digital Economy Lab, 2 April 2026, Pereira, Graylin and Brynjolfsson: The Enterprise AI Playbook
    Read the case on page 63 of the PDF. It does not name the company; Fathom's press page says the case is Fathom, so the link rests on the company's word.
  9. C Fathom AI technology page
    Read in full. Source for the agent fleet, the per-customer databases and the practice count.
  10. C Database of failed startups, local export
    Local export. AI-written summaries, not independently verified. Source for the failed predecessors.
  11. C Fathom AI customer page: Tiger Aesthetics
    Read in full. Source for Tiger as the first customer and its team of about 16 reps.
  12. C Fathom AI blog, 22 April 2026, by Ben Hooten: Introducing Fathom SOS and Fathom BOS
    Read in full. Source for the two product lines.

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