What we do
Four ways we get your team out of manual work.
Every engagement below starts the same way: you show us the task as you do it today, and we scope exactly what replaces it — in writing, with a price and a definition of done. Most pilots ship in two to four weeks.
Book a free demo01 — Custom software
Software shaped around how your team actually works
Web apps, mobile apps and internal tools built to a fixed scope. We start from the workflow you already run — the spreadsheet with 14 tabs, the shared inbox, the form nobody fills in correctly — and design the system that replaces it, not a template with your logo on it.
You review a clickable prototype before we write production code, so the first thing you test is already close to right. When we hand over, the code is yours: repository, tests, deployment pipeline and documentation, with training for whoever runs it next.
What you get
- A discovery workshop and a written spec you sign off on
- A clickable prototype before production build starts
- The working app — web, mobile or both — with role-based access
- Automated tests and a one-command deployment pipeline
- Full source code, documentation and a handover session
Good fit if: your team runs on spreadsheets and email threads, and every off-the-shelf tool you've tried fits about 70% of the job.
02 — AI integration
Copilots and retrieval pipelines wired into your systems
We build AI that answers from your data, not from the open internet. A typical retrieval (RAG) engagement starts with an audit of where your knowledge actually lives — PDFs, tickets, wikis, databases — then an ingestion pipeline that chunks, embeds and refreshes it on a schedule, and a copilot or chat interface wired into the tools your team already opens every day.
Before anything goes live, we build an evaluation set from real questions your staff ask and measure retrieval quality against it. Your data stays in your infrastructure or your cloud account; we set the guardrails so the model cites its sources and says "I don't know" instead of guessing.
What you get
- A data-source audit and an access plan your IT team approves
- An ingestion pipeline: chunking, embeddings, scheduled refresh
- A retrieval evaluation set built from real staff questions
- A copilot or chatbot embedded where your team works
- Usage and cost monitoring with a monthly review
Good fit if: the answers your team needs exist — in PDFs, old tickets and someone's head — but finding them takes twenty minutes each time.
03 — Automation
The morning routine, done before anyone logs in
Order intake from email and PDFs into your ERP. Bank and ledger reconciliation with a short exception list instead of a long spreadsheet. Weekly reports that assemble and send themselves. Follow-ups that go out on schedule without a sticky note. If a job is done the same way every day, we can usually make it run without anyone touching it.
We map the process as it really happens first — including the workarounds nobody wrote down. Then we build the workflow with error handling, retries and a review queue, so when something odd arrives, a person sees it instead of the system silently failing.
What you get
- A process map of the current workflow, exceptions included
- The automated workflow with error handling and retries
- An exception queue so people only review the unusual cases
- Alerts in email or chat when something needs a human
- A runbook and monitoring so you can see it working
Good fit if: someone on your team spends the first two hours of every day copying data from one system into another.
04 — Consulting
A straight answer on where your tech budget should go
Two to three weeks with your stack, your data and your team, ending in a roadmap you can act on. We look at what you run today, what it costs, where the manual work hides, and where AI or automation would pay back — and, just as often, where it wouldn't. Every recommendation comes with a cost estimate and a reason.
We make honest build-versus-buy calls, including "keep what you have." Since 2020 we've done this for retailers, logistics firms and clinics, and the roadmaps that saved the most money were often the ones that cut tools instead of adding them.
What you get
- An audit of your current stack, data and recurring costs
- A prioritized roadmap with cost estimates per item
- Build-versus-buy calls with vendor shortlists where buying wins
- A written readout your leadership can decide from
- An optional quarterly check-in to keep the plan honest
Good fit if: you have budget for "something with AI" but no one you trust to say what, in which order, or whether at all.
How engagements run
Same three steps, whichever service you pick
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Show us the problem.
A free 30-minute call where you walk us through the task as you do it today.
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Get a fixed-scope plan.
A written proposal within a week: what we build, what it costs, what "done" means.
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We ship a working pilot.
Live in two to four weeks. You test it on real work, we adjust, then we hand over.
Questions
Asked on almost every first call
Who owns the code when the project ends?
You do. On final payment we transfer the repository, infrastructure access and documentation to your accounts. There is no licensing fee, no lock-in, and any developer you hire later can pick the project up from our handover docs.
How long does a typical project take?
Most pilots go live in two to four weeks. Larger builds run eight to twelve weeks, split into fixed-scope phases so you see working software at each step. Consulting engagements finish in two to three weeks. You get a dated plan before we start — and since every phase is fixed-scope, delays are ours to absorb, not yours.
Can you work with the systems we already have?
Yes — that is most of our work. We integrate with ERPs, accounting tools, CRMs, spreadsheets and in-house databases through their APIs, or through exports where no API exists. Replacing a system is a last resort we have to argue for in writing, not the default.
What happens to our data in AI projects?
Your data stays in your infrastructure or your own cloud account — we work inside it rather than copying data out. Where a third-party model is involved, we use business terms that exclude training on your data, and the data-source audit at the start of every AI engagement states exactly what is sent where, for your IT team to approve.
Not sure which of the four you need?
That's what the free call is for. Bring the task, we'll tell you which service fits — or that none of them does.
Book a free demo