Paste an Invoice. Watch It Become Data.
This is the same kind of model we would build into your accounting or ordering system. Use the sample, or paste the text from one of your own supplier invoices. Messy formatting is the point.
Runs on a live model. Nothing you paste is stored.
What comes back
Structured data your accounting or ordering system could take directly: vendor, document number, date, each line with quantity and amount, and a note about anything a person should check.
Six Jobs We Would Put AI On Tomorrow.
Each of these has a person doing it by hand today in most businesses we talk to. Each one has an example from the kind of client we work with.
Read the paperwork
Invoices, purchase orders, delivery tickets, applications. AI pulls the fields out and puts them where they go, with a person checking anything it was unsure about. This is the single most reliable use we know of.
A distributor receiving 200 supplier invoices a month stops keying them in by hand.
Draft the quote or the reply
From your own past quotes, price list and notes, AI writes the first draft of a proposal, a follow-up, or a customer reply. Your person edits and sends. The blank page goes away; the judgment stays with you.
A contractor turns a site visit voice memo into a formatted quote in the truck.
Sort and route what comes in
Inbound email, web forms, voicemail transcripts. AI classifies each one, pulls out what matters, and sends it to the right person or system. Nothing waits in a shared inbox for someone to notice.
A property manager stops triaging maintenance requests by hand every morning.
Answer questions from your own documents
Policies, product specs, past projects, the manual nobody reads. Staff ask in plain English and get an answer with the source, instead of interrupting the one person who knows.
New hires at a wholesaler look up product and pricing rules without asking the owner.
Summarize what happened
Long email threads, call recordings, daily reports. AI turns them into what changed and what needs action, so the owner reads a paragraph instead of forty messages.
A dispatcher gets a morning summary of overnight tickets instead of scrolling.
Fill in the gaps between systems
Where two pieces of software do not talk and a person retypes between them, AI plus an integration usually removes the retyping entirely. Often this is the cheapest fix on the list.
Orders from email land in the accounting system without being keyed twice.
AI Is a Very Good Clerk. It Is Not a Manager.
Most of the disappointment with AI comes from putting it on the wrong job. It is excellent at reading, drafting, sorting and summarizing under a person's review. It is bad at running a process alone, and any use where a wrong answer reaches a customer needs far more care than a demo suggests. We will tell you which category your idea is in before we take money for it.
- Run a department without supervision
- Make decisions nobody can audit or explain to a customer
- Replace a process that was never written down in the first place
- Talk to your customers unsupervised where a wrong answer costs you
Measured on Your Data Before You Commit.
A short call or a visit. We want to see the real documents, the real inbox, the real spreadsheet. Twenty minutes usually tells us whether AI belongs here.
We prototype on a sample of your actual data and measure how accurate it is. You get a written scope with a fixed price, and the prototype results, whether or not you go ahead.
The result lands in your accounting, ordering or CRM system with a review step, not in a chat window. Your team keeps working the way they work.
We monitor accuracy after launch and fix what drifts. You own the code and the accounts, and an ongoing arrangement keeps it running.
Frequently Asked Questions
How accurate is it, honestly?
On clean, typed documents like the ones in the demo, extraction is very reliable. On scanned, handwritten or badly formatted documents it drops, which is why every build includes a review step for anything the model flags as uncertain. During discovery we run it on a sample of your real documents and give you the actual number before you commit.
What does it cost?
Discovery starts at $1,500 and produces a fixed proposal for the build, so the real number is in writing before you commit. The build itself depends on how many systems it touches. Running costs for the model are usually small, often less than a single subscription you already pay for, and we show you the estimate in the proposal.
Is my data used to train anything?
No. We use commercial API access where your documents are processed and not retained for training. We will put the specific provider terms in the proposal, and for sensitive data we can keep processing entirely inside your own cloud account.
Do we need to replace our existing software?
Almost never. The useful pattern is AI reading or drafting something, and an integration putting the result into the system you already use. If you are on QuickBooks, a CRM, or a custom ordering system, we build to it.
How long does it take?
A single document-reading or routing workflow is usually live in three to six weeks after discovery. Something that touches several systems takes longer, and we will tell you which yours is on the first call.
We are a small business. Is this really for us?
It is if a person is spending hours a week retyping, sorting, or drafting the same kind of thing. If nobody is, it probably is not yet, and we will say so. The demo above is a decent test: if you have a stack of documents like that, there is a job here.