Why we exist.

Modern small businesses move money through five or six tools that don't agree with each other, and they leave the books in whatever cloud each vendor runs. We built Solomon AI for the founders who think both of those defaults are wrong.

A founder running a 5-to-50-person company in 2026 spends Sunday nights reconciling Stripe against the bank statement. Tuesday afternoon, closing Series A diligence, they open four dashboards and a spreadsheet to answer one question about AR aging and the numbers don't tie. The shape of the problem is older than SaaS. Financial events live in different systems, with different definitions of the same nouns. The shape of the answer in the 2010s was to put all of it in someone else's cloud. We think that answer is finished.

For a decade, the trade made sense. The AI was on cloud servers because that is where it had to be, and putting your books in Ramp or Bill or QuickBooks meant the dashboard could be good. What you paid for the dashboard was your books living on someone else's tenant ID, your vendor list available to whatever the vendor decides to do with it, and an audit trail that depended on whatever export format they gave you when you left.

Why now

The buyer is changing first. A 5-to-50-person company in 2026 is paranoid in roughly this order: losing customer trust, losing payroll runway, losing the right to walk away with their own data. Putting the books in Ramp or Bill kills the third one. Switching vendors means a migration. Acquisition forces a renegotiation. Audits cost an export of their own data from someone else's server. Founders who got burned by this once don't forget it.

The AI is changing alongside. Local 70B-class models running on consumer hardware already match cloud frontier models on the narrow tasks that make up finance work: invoice extraction, AP coding, reconciliation reasoning, dunning copy. By 2028 we expect local models to lead on those four. The constraint that forced finance into the cloud is lifting.

Local-first finance was a real category once. Beancount, Hledger, desktop Quicken were all built on the assumption that the books belong on the operator's machine. SaaS killed the category for a reason. The AI of the 2010s needed cloud scale to be useful, so the books moved. The reason is gone now. We are not inventing a new category. We are restoring an old one with the AI that finally works on a laptop.

What this looks like

The product is a local data plane called Sync and three apps that sit on it. Sync mirrors every financial event in your company into a Postgres warehouse you control: Stripe charges, bank transactions, QuickBooks entries, Notion contracts. Time-traveled. Queryable. Joinable to whatever else you already have.

Eigenn handles the receivables side on top of Sync. Cadense handles payables. Conduitt handles the customer thread. OperatorCamp publishes the field manuals for the operators running this work without a team. The AI on each product reads from your warehouse, not from our database. Nothing the operator looks at is data we have access to. That is the entire point.

The longer arc lives in the master plan: the steps, the timing, where the bet has attack surface, what would prove us wrong. Start there for the architecture. Stay here for the reason.