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AI research agents that keep business and location datasets up to date · United States

Reprompt AI: Revenue, sale and how it was built

Small teamFundedExitB2BBusiness data

Reprompt AI (AI research agents that keep business and location datasets up to date, United States): Acquired by Rippling, November 2026. Evidence grade E: no revenue figure was checked. Team: 2 co-founders in late 2023; team size 3 on its Y Combinator profile, read November 2026. Launched 15 March 2024; sold 32 months after launch.Added 8 November 2026

Outcome
Acquired by Rippling, November 2026
Evidence
E no revenue figure was checked
Launch
15 March 2024
Status
Sold, 32 months after launch
Team
2 co-founders in late 2023; team size 3 on its Y Combinator profile, read November 2026
Outside funding
Y Combinator, Winter 2024 batch (amount not stated in the sources read)
Main channel
Not stated
No revenue figure

What is not verified

No revenue figure and no sale price were found. We looked for a payment-processor profile, a founder interview with a dated figure, a funding announcement and a buyer filing; Rippling's post gives no price. Rippling writes that the team is joining, while Reprompt's own home page says Reprompt has been acquired; this page uses outcome exit under casebook rule 10. The team size of 3 is the Y Combinator profile only. The customers are named by Rippling and by Reprompt, not by the customers, and the home page shows the logos of Data Axle and Matador, and the about page's "Trusted by Industry Leaders" row adds Y Combinator, whose batch Reprompt joined, Robinhood and Mapbox, where the co-founders worked before, and Retool, Instacart, AWS, Rebel Fund, TomTom, Radar, Kalibrate, HGreg and People Data Labs; none has a case study. A reader could look for a Rippling filing or a statement by a named customer. This story is grade E: the business is real and its product, price and customers are described from public pages, but no revenue figure was checked. Aiolum shows it as an idea worth studying, not as proof that it makes money.

Reprompt AI sold AI research agents, programs that use a large language model to plan web searches, read the pages they find and return a structured answer. Its agents keep data about points of interest (POI), the shops, restaurants and other places that appear on a map, up to date, and they run KYB checks (know your business: checking that a company is real, registered and operating at its address) for payment companies.

Lukas Martinelli and Rob Balian founded it in late 2023 and joined Y Combinator's Winter 2024 batch. Their first launch, on 15 March 2024, was a tool to test and fix AI apps; in January 2025 it announced an agent for Foursquare's place data. On 6 November 2026 the software company Rippling announced that the team behind Reprompt AI was joining it, and Reprompt's own home page now says that Reprompt has been acquired by Rippling.

This is a grade E story: no source we read gives Reprompt's revenue or a sale price. Its Y Combinator profile shows a team of 3 people. Rippling named Visa, DoorDash and Tripadvisor as customers, and Reprompt's profile named the mapping companies Radar and TomTom.

Reprompt AI: Acquired by Rippling, November 2026. AI research agents that keep business and location datasets up to date, United States, team of 2 to 10, evidence grade E.
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01

How much did Reprompt AI make, and what was it sold for?

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.

A three-person AI data company whose team Rippling took in 32 months after its first launch; no revenue figure or price was published
FactValueGradeHow we knowSources
Company startlate 2023; 2024 on its Y Combinator profileBRippling's announcement: "Lukas Martinelli and Rob Balian founded Reprompt in late 2023". The Y Combinator profile gives 2024 as the year founded. The earliest Internet Archive copy of repromptai.com is from 23 March 2024.[1, 3, 11]
First public launch, 15 March 2024a tool to evaluate and improve AI apps without codeCY Combinator launch post: trace AI calls, flag hallucinations as bugs, and write prompt overrides. The place-data agents came later.[4]
Team2 co-founders; team size 3CY Combinator profile, read 8 November 2026. Martinelli is CEO and Balian CTO on Reprompt's about page.[3, 12]
FundingY Combinator, Winter 2024 batchBRippling's announcement and the Y Combinator profile. No source we read states an amount or a later round.[1, 3]
Customers namedVisa, DoorDash and Tripadvisor; Radar and TomTomBRippling, 6 November 2026, names the first three. Reprompt's Y Combinator profile says "Mapping companies like Radar and TomTom use our agents". The customers themselves were not read.[1, 3]
Scale of the agents"over 150M AI agents" run; "over 4 trillion LLM tokens" processedBRippling, 6 November 2026, for the agents. Reprompt's blog, 29 May 2026, for the tokens.[1, 7]
Business database, November 2026"200M+ businesses", "+220M rows", 50 enrichment attributesCReprompt's home page, read 8 November 2026.[2]
Published price, July 2026US$5 per 1,000 requests for the Search and Ask APIsCReprompt's blog post of 27 July 2026 by Rob Balian.[5]
Own benchmark, July 202636 of 39 closed places found (92%)CReprompt's test on human-checked places. It reports 25 of 39 for OpenAI Deep Research (o3) and for Gemini 3.5 Flash, 23 for GPT-5.5 and 17 for Claude Opus 4.8. Not checked by anyone else.[8]
Outcome, 6 November 2026team joins Rippling; Reprompt's site says it was acquiredBRippling: "the team behind Reprompt AI is joining Rippling". Reprompt's home page: "Reprompt has been acquired by Rippling." No price was published. Outcome exit under casebook rule 10, because a source says the company was acquired.[1, 2]
Time from first launch to the sale32 monthscalcCalculated: 15 March 2024 to 6 November 2026.[1, 4]

How to read this table: grade B is Rippling's own announcement as the buyer; grade C is Reprompt's own pages and its Y Combinator profile. A "calc" value was computed on this page. No revenue figure exists in any source we read.

Reprompt's only published prices, from its blog post of 27 July 2026 (grade C); the main data products are sold through demos and sales calls
PlanPer month, billed yearly (US$)Per month, billed monthly (US$)Limit
Search API (ranked web results)5 per 1,000 requestspay per request
Ask API (short answer with citations)5 per 1,000 requestspay per request

The address repromptai.com/pricing returned page not found on 8 November 2026. The enrichment, fraud and KYB, last-mile and dataset products show "Get a Demo" and "Book a call" buttons and no public price. The blog post says the Ask endpoint has no separate token surcharge.

02

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

From a tool that tests AI apps to place-data agents bought by Rippling, in about two and a half years. Each entry carries its grade.

  1. Late 2023BLukas Martinelli, earlier a general manager on Mapbox's executive team, and Rob Balian, earlier head of growth at Robinhood, found Reprompt. [1]
  2. 15 March 2024CLaunch on Y Combinator during the Winter 2024 batch: a tool that lets AI teams trace, test and fix their apps without code. [4]
  3. 5 January 2025CPartnership with Foursquare: Reprompt's agent works inside the FSQ Places Engine and accepts a fact only when three separate sources agree. [6]
  4. 27 July 2026CSearch and Ask APIs for other companies' agents. Reprompt's blog lists both at US$5 per 1,000 requests. [5]
  5. 6 November 2026BRippling announces that the Reprompt team joins it to work on Rippling's AI agents. Reprompt's home page says the company has been acquired by Rippling. [1, 2]
03

Why did Reprompt AI work?

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

01

A narrow kind of research

General chat agents answer any question. Reprompt answered a few questions about places, again and again, for millions of rows: is it open, what are its hours, where is the entrance, who owns it. Its own July 2026 test claims it found more closed places than the general agents of OpenAI, Google and Anthropic.

02

Several sources for each fact

The agents read search engines, business directories, official websites, social media and government filings, and in the Foursquare work a fact needed three separate sources. Reprompt measured fill rate, precision and stability, which is how often a repeated run gives the same answer.

03

Expensive models only where needed

Reprompt's May 2026 post says it first runs a task at full depth, then finds the steps that a faster, cheaper model can do, such as summarizing one web page for the main agent.

How it was built

These details come from Reprompt's own blog and pages. They are grade C. [7, 8, 10, 2]

  • A planner agent resolves which place is meant, then chooses research branches: search and browse, routing, aerial and street-level imagery, property data and partner databases.
  • The benchmark post says the agent harness has "over 40 tools at its disposal".
  • Custom source ranking by country and a custom address formatter, because the models handle addresses poorly.
  • Requests go into a queue and workers process them on their own, so millions of POI enrichments run without blocking.
  • Customers reach it through an API, an AI table called the Reprompt AI Workbook, or data files from Reprompt's own business database.

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 Reprompt AI, and why did they fail?

Three companies in our database of failed startups tried to build a business on data about places before large language models could read the web for them. The values below are from that database and are not independently verified.

Died 2007 to 2012Burned US$10.5M

Gowalla

The promise

Check in at coffee shops and other places on your phone and collect badges.

Why it died

Lost to Foursquare's partnerships; Facebook then took the team, not the product.

Competition
Died 2012 to 2014Burned US$2M

Desti

The promise

An AI travel guide that read the web and suggested hotels and restaurants.

Why it died

Users liked the suggestions, then booked elsewhere, so the technology never earned enough.

Unit Economics
Died 2013 to 2021Burned US$15M

Qraved

The promise

Restaurant discovery and booking for Indonesia, with an editorial team.

Why it died

Google Maps took over discovery and super-apps took bookings; COVID closed dining rooms.

Ran Out of Cash

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 three predecessors built consumer apps around information about places, and the database records that Foursquare, Google Maps or other booking sites took their users. Reprompt sold to companies that already had the lists and needed them correct, and its agents did the reading that editors, raters and users had done before.

Gowalla's end matches Reprompt's: a larger company took the team. The difference is that Reprompt's site describes a sale of the company, and the buyer, Rippling, said it wanted the founders to build its own agents, not to run a place-data business.

05

Can one person copy Reprompt AI now?

Hard for one person; the method is open.

Reprompt needed founders who had run search and data-labeling teams, a large database and enterprise sales to Visa-sized customers, as Rippling and Reprompt's own pages describe. The method a small team can reuse is one narrow research question, asked by an agent across many web sources, measured against a human-checked sample.

Where it is still open: Other lists that go out of date: supplier and vendor data, store hours for delivery apps, licence and registry checks in countries with poor public data.

  1. 1Choose one fact that companies must check again and again in a large list, such as whether a business is still open.
  2. 2Build an agent that needs agreement from several sources before it answers.
  3. 3Measure fill rate, precision and stability on a sample that people have checked.
  4. 4Sell it as an API priced per request, and run the cheap steps on smaller models.

What could go wrong for Reprompt AI?

The risks are the mirror image of the causes above.

What is not verified

No revenue figure and no sale price were found. We looked for a payment-processor profile, a founder interview with a dated figure, a funding announcement and a buyer filing; Rippling's post gives no price. Rippling writes that the team is joining, while Reprompt's own home page says Reprompt has been acquired; this page uses outcome exit under casebook rule 10. The team size of 3 is the Y Combinator profile only. The customers are named by Rippling and by Reprompt, not by the customers, and the home page shows the logos of Data Axle and Matador, and the about page's "Trusted by Industry Leaders" row adds Y Combinator, whose batch Reprompt joined, Robinhood and Mapbox, where the co-founders worked before, and Retool, Instacart, AWS, Rebel Fund, TomTom, Radar, Kalibrate, HGreg and People Data Labs; none has a case study. A reader could look for a Rippling filing or a statement by a named customer.

Competition

Ballerine, another story on this site, sells AI agents for merchant risk checks to payment companies, which overlaps with Reprompt's fraud and KYB product. Reprompt's own July 2026 benchmark compares it with the general research agents of OpenAI, Google and Anthropic, which also search the web.

Dependence on model providers

Reprompt's May 2026 post says it had processed over 4 trillion model tokens, that the price of hosted small models was rising as providers retire older ones, and that it was testing self-hosted and open-source models. The sources we read do not name the providers it used.

Data about business owners

The products research the businesses in public web pages, social media and filings, and two pages offer questions such as "who the owner is" and "Does owner own short-term-rental properties?". For a small business the owner is often one person. The sources we read do not say how such personal details are handled.

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 Rippling blog, 6 November 2026, by Albert Strasheim: Reprompt AI is joining Rippling to build the future of agents
    Read in full. The buyer's own announcement. Source for the founding date, the founders, the customers, the agent count and the team joining.
  2. C Reprompt home page, read 8 November 2026
    Read in full. Source for the acquisition banner, the products, the database counts, the logos and the owner question.
  3. C Y Combinator company profile: Reprompt, AI Agents for Location
    Read the profile data in the page: description, year founded, team size, location and founders.
  4. C Y Combinator launch post, 15 March 2024: Reprompt AI, Helping AI apps get to production quality 10x faster
    Read in full. Source for the first product and the founders' earlier work.
  5. C Reprompt blog, 27 July 2026: Introducing Search and Ask APIs
    Read in full. Source for the only published prices.
  6. C Reprompt blog, 5 January 2025: Announcing Our Partnership with Foursquare
    Read in full. Source for the Foursquare agent and the three-source rule.
  7. C Reprompt blog, 29 May 2026: Building a location deep research agent
    Read in full. Source for the architecture, the token count and the model costs.
  8. C Reprompt blog, 8 July 2026: Reprompt outperforms OpenAI, Claude, Gemini on hard places research tasks
    Read the method and the closure results. The company's own test.
  9. C Reprompt product page: Fraud & KYB, read 8 November 2026
    Read in full. Source for the KYB attributes and the owner question.
  10. C Reprompt blog, 26 January 2026: Web agents on 200M+ POI data
    Read in full. Source for the agents' web sources, the metrics and the queue of workers.
  11. C Internet Archive availability record for repromptai.com, earliest copy
    Read the record: the closest copy to 1 January 2020 is from 23 March 2024.
  12. C Reprompt about page, read 8 November 2026
    Read in full. Source for the CEO and CTO roles.
  13. C Database of failed startups, local export
    Local export. AI-written summaries, not independently verified. Source for the failed predecessors.

Run this company? Send corrections or a verified figure to aiolum@livyden.com

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