AI & Intelligent Automation
Language models and automation put to work on a specific job, with the engineering around them that makes the result dependable.
The model is rarely the hard part. The hard parts are getting the right data in front of it, checking what comes out, and fitting the result into the way people already work.
We start by asking where AI would actually save time or money in your business, and we are comfortable answering "not here".
What we take on
AI features in existing products
Search, summarising, drafting and classification added to software you already run.
Retrieval over your documents
Answers grounded in your own manuals, tickets and records, with the sources shown (RAG).
Agent workflows
Multi-step tasks handed to a model with tools, limits and a human check where it matters.
On-device and private AI
Recognition that runs in the browser or on the device, for data that should not leave it.
How an engagement runs
Scope
A conversation, then a short written plan: what gets done first, what it costs, and what is deliberately left out.
Build
Working results early and often. You see progress in something running, not in status reports.
Ship
Deployment, monitoring and backups are part of the job, not an afterthought.
Hand over
Your code, your accounts, and documentation written for whoever maintains it next.
What we use
Work that backs this up
Invoice and barcode recognition that runs in the browser, so the photos never leave the device.
Inventyl
Camera-first inventory for small business
An installable web app for shops that have outgrown spreadsheets: scan barcodes to take stock, photograph a supplier invoice to restock, and keep counting when the connection drops.