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Finance, risk and compliance

Bookkeeping, invoices and receipts, expense tracking, payments and tax, loan and insurance documents, fraud and compliance checks for banks and fintechs, due diligence for deals, grant applications and scam checks.

Finance, risk and compliance holds 30 of the 603 stories on Aiolum: 6 run by a solo founder and 24 by a team of 2 to 10. Together they report US$10M in verified outcomes; the largest is Poetic, At least US$10M a year run rate, 2025. 3 headline numbers carry evidence grade A (disclosed or verified), 0 grade B (independent press) and 1 grade C (founder claim), 8 are grade D (reported, not verified), and 18 have no revenue figure (grade E). The median story reached its headline number 20 months after launch. The founders are in 15 countries, most often United States and Germany. The most common main channel is cold outreach (4 of 30). The tools named most often in their sources are Next.js (16), Google Analytics (10) and Vercel (10).

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Evidence gradesA disclosed or payment-verifiedB independent pressC the founder's own figuresD reported, not verifiedE no revenue figureHow we verify

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The revenue trend compares the latest months in the sources with the months before them. Falling means revenue is about 15% or more below the best recent months, or the sources report a fall. The headline number is the yearly figure or the sale value on each card.

30 of 603 stories shown

AI invoice and receipt collection for small companies and accountants · Spain

Tailride

Evidence A
$19K/mo, then new owner

Solo founder · sold 17 months after launch

It solved one narrow and repeated task that every company has at the end of each quarter: find all invoices and give them to the accountant. It read the invoices where they already were, in the inbox and on supplier websites, instead of asking people to forward them, and it let customers write their own checking rules in plain language. Stripe data shows monthly revenue rising from US$12,631 in November 2025 to US$18,970 in January 2026.

5 grade-A facts · 4 that failed before it
AI bookkeeping chatbot inside LINE for small shops · Thailand

Zendai

Evidence A
$1.3K MRR, Stripe-verified

Team of 2 to 10 · 33 months after launch, revenue falling

The product goes where the customers already are: a shop owner does not install a new app or learn accounting software, but writes into a chat. The founder wrote of having worked as a data scientist at a microloan company and of running a café, so the founder knew both the bookkeeping problem and the reason banks ask for records.

7 grade-A facts · 3 that failed before it
AI receipt scanner and expense tracker app for iPhone and Android · Singapore

ReceiptGenie

Evidence A
$10.6K verified, 19 months

Solo founder · 19 months after launch, revenue growing

The founder, a digital nomad, had collected more than 1,000 receipts from many countries to track his own spending, and built the app for that use. It reads every line item instead of only the total, which matters for travellers with receipts in foreign scripts and currencies. Small, steady releases (25 versions between 21 January and late October 2026) and a translation of the app into 52 languages widened the market without a team.

7 grade-A facts · 4 that failed before it
AI process automation for banks and insurers · USA · Funded

Poetic

Evidence C
$10M+/yr run rate

Team of 2 to 10 · 24 months after launch

It picked work that large regulated companies had failed to automate for years and that tolerates almost no errors. Instead of letting a model decide each step, it turns the expert's procedure into fixed program steps, which makes the result predictable and cheap to run. A few large customers, sold directly, can pay for a very small team.

Every number graded · 3 that failed before it
AI bookkeeping, VAT-return and annual-accounts software for small German GmbHs and UGs, with trained accountants checking the AI's bookings · Germany · Funded

mika

Reported, not verified
€1M+ annual revenue reported

Started small, grew after funding · 25 months after launch, revenue growing

Every GmbH and UG in Germany must keep books, file VAT returns and produce annual accounts, and most pay a tax adviser's office to do it, the company's press release says. mika puts AI on the routine part, keeps people on the checking, and sells it as a monthly subscription that the price page lists from €49 net. It chose one narrow customer, the small limited company without its own finance staff, and the customer count grew from about 400 at the start of 2026 to more than 750 in September 2026, the company said.

Every number graded · 3 that failed before it
AI platform that chases late B2B invoices · France · Funded

Cleavr

Reported, not verified
$1.12M ARR reported

Team of 2 to 10 · 7 months after launch

Chasing late invoices is repetitive work that finance teams do by hand in spreadsheets and email. Cleavr connects to tools that companies already use, such as Pennylane, Stripe and SAP, so a customer can start without a migration, and the company says setup takes under a day.

1 grade-A fact · 4 that failed before it
AI cattle identification for livestock insurance and loans · Bangladesh · Funded

InsureCow

Reported, not verified
$900K+ total revenue

Team of 2 to 10 · 47 months after launch, revenue growing

Bangladeshi insurers rarely cover cattle because they cannot tell one cow from another, so claims are easy to fake. A biometric identity removes that problem for the insurer and the lender, and the farmer gets access to insurance and loans that did not exist for his main asset.

Every number graded · 5 that failed before it
AI agent for public grant applications · Portugal · Funded

Granter

Reported, not verified
€400K sales in 9 months

Started small, grew after funding · 26 months after launch

Applications for European and national public funds are long, bureaucratic and usually written by specialist consultants. Granter put the consultant's work into an AI agent that a company can use itself, started in Portugal, where EU funds are a large part of company financing, and then won two large European startup competitions in seven months.

Every number graded · 3 that failed before it
Expense-tracking phone app with natural-language entry · Germany

MonAi

Reported, not verified
$35K/mo MRR, reported

Team of 2 to 10 · 34 months after launch, revenue growing

The founder says the app sat at about US$300 a month for a year and a half, until a content creator in Colombia found the founder's X link inside the app and proposed a partnership. According to the founder, three story-driven videos a month in Spanish, paid with a share of the profits and a fixed retainer, took the app to more than US$35,000 a month in about a year.

Every number graded · 5 that failed before it
AI document reading and credit analysis for banks and lenders · Indonesia · Funded

Fineksi

Reported, not verified
$20K MRR reported

Team of 2 to 10 · 35 months after launch, revenue growing

In Indonesia a credit analyst still reads a pile of PDFs, scans and phone photos by hand for each loan. Fineksi sells the reading step to the lender, so the analyst checks results instead of typing numbers. The accelerator Accelerating Asia reported in December 2025 that the founders had banking and technology experience and bank customers such as Permata Bank and Hana Bank.

Every number graded · 4 that failed before it
Merchant of record with AI pricing and billing agents for solo founders · Estonia

AgentaOS

Reported, not verified
$9.5K/mo, one source

Solo founder · 7 months after launch

The founder had spent years in payments and had just failed with a stablecoin wallet for AI agents under the same name. In August 2026 he relaunched the brand as a merchant of record aimed at sellers in countries the big processors skip, with the first country guides written for the Western Balkans. The company's about page quotes an Indie Hackers interview of 6 October 2026 whose title says the relaunched business reached US$9.5K of monthly recurring revenue in two months, and its home page counts more than 400 sellers and 1,400 payments since August 2026.

Every number graded · 5 that failed before it
AI bank statement and financial document converter · United States

LedgerBox

Reported, not verified
$1K/mo reported

Solo founder · 7 months after launch

Bookkeepers still receive many bank statements as PDF files and type the transactions into accounting software by hand. The founder is a QuickBooks consultant who had this problem himself. The product does one specific job, metered by the page, and has a separate plan for bookkeeping firms that is counted by client.

Every number graded · 3 that failed before it
AI controller software for CPA and fractional CFO firms · USA

AgentLink

No revenue figure
3 design-partner firms

Solo founder · 10 months after launch

The founder first built a forecasting tool for business owners and learned that most owners hand their finances to a fractional CPA or CFO. He changed the buyer to those firms. He found three firms willing to act as design partners, one through his network and the JumpStart support program and two at an accounting conference, and builds with them every week.

Every number graded · 2 that failed before it
AI that extracts cited, checkable answers from documents for audit, compliance and M&A teams · Sweden · Funded

Normain

No revenue figure
Big Four customer signed

Team of 2 to 10 · 20 months after launch

Consulting and accounting firms do the same document reviews again and again, and chat assistants give a different answer each time with no page reference. Normain sells the opposite promise: the same input gives the same output, and every finding points to its source, so a professional can sign off on it.

Every number graded · 3 that failed before it
AI that turns insurance and finance document packages into checked, structured records · United Kingdom · Funded

Parsewise

No revenue figure
Three named customers

Team of 2 to 10 · 18 months after launch

The two founders had seen the same problem from two sides: one at Palantir building document pipelines for insurance clients, one at Bain doing due diligence by hand. They built a layer on top of large language models that checks the whole document set and shows the source of each answer, which regulated buyers need before they trust the output.

Every number graded · 3 that failed before it
AI agents that analyse client data for M&A and corporate finance advisors · United Kingdom · Funded

Intriq AI

No revenue figure
Live, demo-only

Team of 2 to 10 · 31 months after launch

The founder spent about ten years in consulting and saw every new engagement start with someone assembling the client's data by hand. She built Intriq to do that analyst layer, so that advisors start from the data instead of from zero.

Every number graded · 3 that failed before it
AI scam check for messages, links, screenshots and phone calls · Canada

Vraust

No revenue figure
50+ active users claimed

Solo founder · 4 months after launch

Most scam victims find out only after the money has left. Vraust puts the check before the payment or the reply, when a person still has time to stop. The founder first built a fraud tool for Canadian banks and then turned it into a consumer app; its pricing page lists a free plan and paid plans from US$9.99 a month.

Every number graded · 3 that failed before it
AI agents that run due diligence for venture and private-equity investors · Canada

Acephalt

No revenue figure
Beta with investor firms

Team of 2 to 10 · 7 months after launch

Due diligence on one private company can mean hundreds of files, and small investment teams do most of the reading and spreadsheet checking by hand. The founder studied computer science and financial engineering and built a tool that splits this work across specialised agents, sold to lean VC firms and family offices.

Every number graded · 3 that failed before it
AI agents for merchant risk checks at payment companies · Israel · Funded

Ballerine

No revenue figure
50+ enterprise customers

Started small, grew after funding · 50 months after launch

Payment companies must check every merchant before and after onboarding, and card networks fine them when a merchant sells banned goods or launders transactions. The founders started with an open-source toolkit for these checks in 2022 and moved to AI agents that do the analyst's research, with a Mastercard certification that the company says can reduce fines.

Every number graded · 3 that failed before it
AI agents that investigate fraud and compliance alerts for banks and fintechs · United States · Funded

Socratix AI

No revenue figure
Money20/20 award winner

Team of 2 to 10 · 12 months after launch

The CEO worked on fraud detection and investigation tools at DoorDash and Unit21 before she started the company, by the Y Combinator profile. She saw analysts move between many tools by hand for hundreds of alerts a week, and large language models made it possible to write an agent that does the routine part of that work and explains each step.

Every number graded · 3 that failed before it
AI business valuation and exit planning platform for owners of small and medium businesses · Canada · Funded

Optionality

No revenue figure
1.5K+ businesses valued

Team of 2 to 10 · 20 months after launch

The founder had sold several companies, one of them to the private equity firm KKR, by the company's About page, and found each time that owners had little visibility into what their company was worth or who might buy it. Large language models made it possible to turn financial statements and transaction data into a written valuation report in minutes, so a small team could offer a free first valuation to owners and use it to reach them years before a sale.

Every number graded · 3 that failed before it
Search engine for small businesses for sale, with AI analysis of the sale documents · United States

DealStack.ai

No revenue figure
14K+ buyers claimed

Team of 2 to 10 · 54 months after launch

The home page says that buyers "spend months filtering bad leads across dozens of platforms, reading dense CIMs manually, and getting ignored by brokers who don't know them". UpNext World repeated this problem in May 2026: buyers review "dense financial documents" across "fragmented platforms".

Every number graded · 2 that failed before it
AI product-compliance assessment for manufacturers: finds the regulations a product triggers before it ships · Sweden

Certean

No revenue figure
Web Summit PITCH startup

Team of 2 to 10 · 13 months after launch

A manufacturer that sells one physical product in many countries must find every law that the product falls under: a battery, a radio module or a laser each adds its own rules. This work is usually done by hand or by consultants and can take months. Certean says it automates the assessment and keeps it current when the rules change.

Every number graded · 2 that failed before it
AI agents that test audit evidence and prepare workpapers for audit firms, in a web app and in Excel and Word · United States · Funded

Punchcard

No revenue figure
Named audit-firm customers

Team of 2 to 10 · 36 months after launch

In a typical audit, much of the time goes into requesting documents from the client, matching each file to a sample item and copying values into a workpaper before any judgment is made. The founder audited at Ernst & Young and says this is the work he left the profession to avoid. An agent that does the matching and shows its sources lets a reviewer check the work instead of redoing it.

Every number graded · 2 that failed before it
AI coworker that prepares work for accounting firms · United Kingdom · Funded

Combinely

No revenue figure
100+ firms, self-reported

Team of 2 to 10 · 18 months after launch

Two co-founders, one from Deloitte and one from Google, started it in 2025 inside Y Combinator. The first version, in May 2025, answered client emails, because, the founders wrote, accountants spend 30% to 40% of the day in Outlook. By October 2026 it ran whole workflows from collecting documents to a prepared return, sold at one price per user with every agent included.

Every number graded · 2 that failed before it
AI platform for private equity due diligence and deal research · United Kingdom · Funded

Capsa AI

No revenue figure
Series A at 14 people

Started small, grew after funding · 27 months after launch, revenue growing

One co-founder had worked on more than 50 due diligence processes in private equity and investment banking, the other had built machine learning products. They launched to real funds four weeks into an accelerator, sold only through their own sales work, and kept customers: the company was cash flow positive after about 1.5 years, it said, before it raised a Series A.

Every number graded · 2 that failed before it
AI finance operating system that reads the ERP, DATEV and CRM data of company groups and answers controlling questions · Germany · Funded

ARC Intelligence

No revenue figure
5 named customers

Team of 2 to 10 · 19 months after launch, revenue growing

Groups that grew by buying companies often run a different ERP or accounting system in each entity, so the finance team exports data to Excel and builds every report by hand. ARC sells a layer on top of those systems instead of a replacement: its home page says it is connected in 24 hours, with no migration. Private equity owners, who want the same figures from every company they hold, have brought it into their portfolio companies, as Startbase reported and one case study states.

Every number graded · 3 that failed before it
AI co-pilot for statutory audits: scores the risk of every ledger line and prepares the auditor's working papers · Germany · Funded

AUDAVIS

No revenue figure
6 named audit firms

Team of 2 to 10 · 21 months after launch

Auditors usually test a sample of bookings, and preparing client data for analysis takes data engineers or days of spreadsheet work. AUDAVIS sells the automatic preparation and a risk score for every line, so small and mid-sized audit firms without their own IT department can test the whole ledger from the first day of the audit.

Every number graded · 3 that failed before it
AI platform that reads insurance carrier documents for Canadian group benefits brokers · United States · Funded

Lucite

No revenue figure
Acquired by Sterling Brokers

Team of 2 to 10 · sold 19 months after launch

It did one specific job, reading the documents that Canadian group benefits insurers send to brokers, and one of its three co-founders had worked more than 35 years as a benefits advisor. Its buyer was also its customer: Dealroom News reports that Sterling Brokers was an early partner and one of Lucite's largest customers before the deal, and that Sterling bought it to open its own administration platform to independent brokers.

Every number graded · 3 that failed before it
AI agents for carrier-bill audit, customer invoicing and collections at freight brokers and 3PLs · United States · Funded

Lighthouz AI

No revenue figure
40+ broker customers

Team of 2 to 10 · 18 months after launch

Freight billing is a stack of PDFs, scans and emails in different formats, and broker accounting teams process it by hand. The founders, an AI professor and an AI engineer, tried two other products first and then chose one industry with this paperwork. In its launch post of 22 December 2025 the company said that brokers using it invoice customers within 24 hours of delivery.

Every number graded · 3 that failed before it
More stories coming

The next verified one-person AI business goes here. Same structure, same evidence grades.

Every number on these cards carries an evidence grade. How Aiolum verifies explains the evidence grades and the five parts of each story.