What we build
Software for the way your business actually works: the screen your team works in, the queue it feeds, the system it writes to.
- Web applications and internal tools — booking engines, member areas, dashboards, and the tool that replaces a shared spreadsheet and a lot of goodwill.
- Integrations — the software you already pay for, talking to each other instead of through someone’s inbox.
- Data pipelines — getting the data where the model and the people both need it, with a record of where it came from.
Everything is built as small as the problem allows, ships with a deploy you can repeat, and is documented so the next developer isn’t doing archaeology. Most app work starts as a Build Sprint.
Where AI fits
AI is one part of the software, not a separate project. Most of its value for a business your size is unglamorous. It reads the forms, invoices, applications and emails your team currently retypes. It answers the questions staff ask each other twenty times a week, from the documents you already have. It sorts, tags and routes the queue so a person starts with the hard cases instead of the easy ones.
- Extraction and classification — turn a pile of unstructured documents into rows you can filter, with a confidence score on every answer.
- Assistants over your own content — policies, manuals, past proposals, product data — that cite where each answer came from.
- Automation between systems — the email that should become a ticket, the booking that should become an invoice, the report nobody wants to assemble.
- Private deployments — when data shouldn’t leave your walls, open models run on infrastructure we operate.
How an engagement runs
- The job, written down. What the work is today, who does it, what a wrong answer costs. If a rule or a spreadsheet solves it, the engagement ends here and you’ve paid for an afternoon.
- Tests before a prototype. Real examples with known right answers, so “it works” is a number rather than a feeling — for the app and, where there is one, the AI feature.
- A small build, measured. Working software in your accounts early, and for AI: accuracy against the test set, cost per item, and the cases it should hand to a person.
- Into the software your team uses — not a new tab they have to remember — with logging, and for AI, cost limits and a way to switch it off.
What you won’t get
A chatbot bolted to your homepage because a competitor has one. Claims we can’t measure. A system that quietly sends your customers’ data to a vendor you didn’t choose. Strategy decks and AI policy are our sister company’s work — Signal & Soil — and we’ll say when you need that first.
