Jurisphere: Revenue, team and how it was built

Team of 2 to 10 · sold 17 months after launch

Four founders, two of whom had built the drinks-delivery start-up Winelivery, looked for a profession that works with a large, fast-changing body of rules and had not yet adopted AI, and chose Italian accountants and labour consultants. They tested a first version with practitioners and sold monthly subscriptions. In October 2025 TeamSystem, an Italian maker of software for accountants, bought the majority of the company; its press release said Normo.ai had €1.3 million of revenue in 2025.

Team of 2 to 10 · 15 months after launch, revenue growing

It sells one narrow job to one profession in one country: missed calls at small Belgian law firms. The site, the blog and the terms are written for lawyers at the Belgian bars, in French, with answers about professional secrecy and GDPR that this buyer asks first. A small firm pays a fixed 90 euros a month instead of a part-time secretary.

Team of 2 to 10 · 6 months after launch

The founders are lawyers who built the legal departments of two Berlin startups, and the CEO writes that he knows the frustration with old legal software from that work. LawX replaces the whole office system instead of adding one more AI tool, it charges one price per user for the whole team, assistants included, and every AI suggestion waits for a person to approve it. tech.eu reported in May 2026 that the next step was the broader law firm market.

Team of 2 to 10 · sold 28 months after launch

Three founders built it without outside money in 2023, and the first message, that it replaced lawyers, scared the customers away. They changed it into an assistant for lawyers, connected it to the Spanish official gazette and court decisions, and had it take the Spanish judiciary entrance exam in front of a notary. According to Merca2, that public test turned a handful of customers into hundreds a month. Doctrine, a French legal AI company, bought it in February 2026.

Team of 2 to 10 · 6 months after launch

The founder is a New York trial attorney with about fifteen years of practice, and the company's pages say he built the platform inside his active trial practice and wrote the prompts and templates himself. General legal AI tools are not built for one task such as contested litigation; this one is built only for that. Its pricing page says usage is designed to be passed to clients as a disbursement, like research time on Westlaw or Lexis.

Team of 2 to 10 · 3 months after launch

It is built for one kind of legal work, litigation, by a co-founder who practiced it. General AI chat tools have produced invented case citations that courts have punished, and Litmas AI sells a check of every citation against real court opinions as its main feature. The company stated that its demand came mainly from inbound marketing, and it priced per case so that small and contingency-fee firms can start small.

Started small, grew after funding · 28 months after launch, revenue growing

German lawyers, tax advisers and doctors are bound by professional secrecy and the GDPR, so many of them could not paste client data into a US chatbot. Logicc sells the same leading models with the contracts, hosting and certificates that these buyers need for approval, at a price per user per month.

Solo founder · 39 months after launch

It launched in October 2021 with one narrow promise, write SQL without knowing SQL, on OpenAI's Codex and GPT-3 models and a no-code app builder. It kept its prices low, built a site of more than 700 pages, among them SQL lessons, templates and comparisons, and added what a general chatbot does not have: a live, read-only connection to the customer's database. Its recurring revenue, as the founder reported it, doubled in 2024 to about US$10,000 a month.

Started small, grew after funding · 14 months after launch

Running a large model fast needs performance engineers, and the founders write that only a few hundred people in the world can deeply optimize accelerator hardware. Wafer tries to do that work with AI agents, on AMD as well as NVIDIA GPUs, and to keep doing it after a deployment goes live instead of tuning it once.

Team of 2 to 10 · 1 months after launch

The founders cut a hard idea, an AI that understands a whole software product, down to a smaller one: an AI that only has to show the product. Co-founder Toni López told Valencia Plaza that the product launched during Y Combinator, gave 2,000 demos on its first day and reached US$31,000 in monthly recurring revenue in three weeks. That is one founder statement, reported once.

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.

Started small, grew without outside funding · 29 months after launch, revenue growing

The founders came from digital marketing agencies, and their first customers were people from the CEO's former agency team, who now work in the marketing departments of large Turkish companies. In 2026 the company rebuilt its dashboard product around the Model Context Protocol, so that general AI assistants can work on live ad data, and opened it to everyone with a free plan.

Solo founder · 6 months after launch

The founder is a home inspector who, the company says, paid for six separate tools that did not share data. He built one app for the whole job and lists a lower price than the market leader, Spectora. The AI tools write the paragraphs that inspectors otherwise type again for every house.

Team of 2 to 10 · 6 months after launch

The founders worked as dispatchers at home-service companies before they built it, and they say dispatch decides how much a shop earns but runs on gut feeling. The software assigns jobs by skill, location, availability and close rate instead of by who is free.