You should be able to ask your business a question and trust the answer.
The problem
Your data is real and it already exists. It just lives in five places that do not talk to each other. The point of sale, the accounting system, a folder of spreadsheets, the e-commerce platform, a supplier's emailed price lists. Answering a basic question about your own business means someone spends a day in Excel, and by the time the answer arrives, the question has changed.
The real problem is simpler. You cannot see your own business.
What we build
We unify everything you already have into a single system you own. Underneath, the work is unglamorous and we are proud of that. Extraction from every source, reconciliation so that a customer is the same customer everywhere, and tie-out against your accounting so the numbers are trustworthy before anyone queries them. On top sits a semantic layer that lets you ask plain-English questions and get honest answers instantly.
Because you own the system, it plugs into whatever AI tools you use now or adopt later. Claude, ChatGPT, your own models. The system is built to outlast any one vendor's moment.
What you get
One place where your business is visible, queryable, and correct. A foundation that makes every future automation, forecast, and pricing decision better.
And an asset on your side of the ledger. The pipelines, the warehouse, and the semantic layer run in your accounts, and nobody meters your access to your own numbers.
What it looks like in practice
A specialty retailer doing $12M a year sold through two stores, an e-commerce site, and a growing wholesale channel, with the numbers for each living in a different system and a controller's spreadsheets holding it all together.
Closing the month took the controller two full days of exports and copy and paste. The same product carried three different names across systems, so channel margin was an estimate, and when the owner asked which wholesale accounts were actually profitable, the honest answer was that nobody knew.
We extracted every source into one warehouse the company owns, matched products and customers across systems, and tied the totals out against the books month by month until everything agreed. A semantic layer on top answers plain-English questions, like which wholesale accounts slipped this quarter, with numbers that reconcile to the accounting.
The monthly close package now assembles itself in under an hour, and the numbers match the books because they are built from them. Wholesale margin turned out to be four points lower than anyone believed, which led to repricing two accounts. The controller spends reporting week on analysis instead of assembly.
A representative engagement, anonymized
Where it fits in a Quarter Plan
Five to eight weeks
Typical build time
Usually a first-quarter foundation. Sources come together over the first two months, with a leadership report running by the end of the quarter. Forecasting, pricing, and agents build on it in later quarters.
Tell us where AI should be paying off in your business.
In 45 minutes we will tell you where we see the opportunity and whether we are the right fit.