Structure before software. We start with an audit to find what's worth building. Then we build it, integrate it with your tools, and monitor and improve it in production. Sometimes the answer is that you don't need AI. We'll tell you that too.
30 minutes, no demo, no slides.
Figures in the film: RAND, analysis of 2,400+ AI initiatives, per 100 projects, rounded. The scoring rows are an illustrative example.
Most AI projects don't fail on the model. They fail on the process nobody mapped.
Out of a hundred AI projects, a third never reach production. More than a quarter ship without delivering value. One in five pays back: 80.3% of AI projects miss their intended value.
So we start where they fail. Diagnosis first. Build second.
Every use case is scored on impact, feasibility, cost and risk. The verdict follows the score, not the sales pitch.
Every diagnosis has four possible endings: process change, automation, an AI system, or build nothing. Only one of them is AI. Sometimes the right answer is to build nothing.
When we do build, agreed tests decide when it ships. Not a demo.
Book a free thirty-minute review. If you don't need us, you'll hear it on the call.
The same order, invoice or customer typed into two or three systems.
Data integration → Tools that do not talkERP, CRM and file shares that each hold part of the truth.
Data integration → Documents nobody can findThe answer exists somewhere. Finding it costs more than rewriting it.
AI, where it adds value → Repetitive tasksChecks, exports and reminders that follow the same rules every time.
Automation →Repetitive work handled by rules that give the same result every time. No model needed.
See what it involves → Data integrationYour ERP, CRM and file shares kept in sync, so nobody retypes data between screens.
See what it involves → Custom applicationsA small internal tool built around how your team works, when no product fits.
See what it involves → AI, where it adds valueKnowledge assistants and agents, built only where language or judgement is the real work.
See what it involves →Answers only from documents the person asking is allowed to open.
Dropped: no access
Use whenPeople need answers from documents with different access rights.
The agent prepares the action. A person decides whether it runs.
If no: it stops
Use whenThe action touches money, customers, or records.
Agreed test cases decide when a system is ready, not a demo.
Fail: fix and run again
Use whenBefore anything reaches production.
Five phases. The second one can conclude that you should build nothing. That is a valid result, and the cheapest one to reach.
Client missions appear here once the client agrees to publication. Until then, what you see is our own work, labelled as such.
Who approved the 2026 commission changes?
Retrieved 3 passages · checked against your access
Approved by the leadership team in March, effective from Q2. 12
1 document withheld: outside your access.A knowledge assistant that checks every retrieved passage against the asker's live permissions before the model sees it. No citation, no answer.
“I would rather tell you in week three that you don't need AI than bill you for finding it out in month nine.”
Pick a time. You leave the call with an honest answer, even if that answer is "not yet".
Then that is the deliverable, and it is worth what you paid for it. Chasing technology instead of an outcome is the most cited cause of AI project failure. We would rather tell you early.
It depends on how many processes are in scope and how scattered your data is, so we price it after the first call rather than guessing in public. Scope, duration and deliverable are fixed before anything starts.
It is thirty minutes on where you actually are and whether we are useful to you. If the honest answer is that you do not need us yet, you will hear it on the call.
You probably do not need us for the build. You may need us for the diagnosis: your team is close to the systems and far from the comparison set.