01AI & Data
The model, the pipelines, and the quality and lineage work that decides whether anything downstream can be trusted.
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AI & Engineering
We build the system and we change the work around it. Most firms do one of those.
Data platforms, integration, model deployment and the governance underneath — delivered by the same team that redesigns the decision the output is meant to inform.
The practice
We design, build and run what sits under a business decision: the pipelines, the integrations, the model, the monitoring. Then we rebuild the decision itself, because an accurate answer delivered into an unchanged process changes nothing.
The distance between a pilot and an operating model is rarely technical. It is a question of who owns the call, what happens when the model is wrong, and whether anyone redesigned the workflow to use the answer. A model nobody trusts is a model nobody uses. That distance is the work.
Our approach
Three things we do differently.
Value first, model second
We start from the decision the model is meant to change, not from the model. If no decision changes, the engagement does not start — and we will tell you that in week one rather than month six.
Engineering as the constraint
Almost every stalled pilot we are handed is stalled on data and integration, not on the model. The unglamorous layer is where the schedule actually lives.
Built to be operated
The handover target is your engineers running it without us. That shapes the architecture from the first week, and it is the reason we work alongside your team rather than in a room down the corridor.
How we help clients deploy
Five steps, in this order, every time.
The order is the method. Most programmes invert steps two and three — they build the workflow around a model whose inputs nobody has validated — and that is the single most common reason a pilot never reaches production.
Where each step lands in the stack
# the one call this engagement is allowed to changedecision: credit_line_increaseowner: vp_risk_operationsbaseline: manual_review_rate: 0.41 cycle_time_hours: 36success_test: manual_review_rate: "< 0.29" loss_rate_delta: "<= 0 bps"review_cadence: weekly, with the owner # if none of these move, the engagement stops here.
Step 01 of 05
Pick the decision
One decision, named, with an owner and a measurable before-state. Not a use-case inventory and not a capability map — a single call somebody makes today that would be made differently with a better input.
What comes out of it
- A named decision and the person accountable for it
- The current baseline, measured before anything is built
- A written test for what “better” means
Where this goes wrong: a workshop produces forty use cases ranked by a scoring matrix nobody believes, and the programme starts on whichever one had an available sponsor.
Runs on its own. Click any step to hold it there.
What we do
Explore AI & Engineering services.
Most engagements start as one of these and grow into a second. None of them are productised — the shape is set in the first two weeks.
02Platform & Cloud
The estate the workload runs on, sized to what it actually costs rather than to what the reference architecture assumes.
03Engineering Delivery
Shipping to production and operating it afterwards — not handing over a repository and a diagram.
04AI Governance
Built for the day something goes wrong, because that is the day it gets read.
Our thinking
What we pride ourselves on.
Three of these are true of every Taidou engagement regardless of practice. They are also the three things we are most often told are unusual — which says more about the industry than about us.
The person who scopes it runs it.
There is no handoff between the team that wins the work and the team that does it. If you met someone in the first conversation, you will still be dealing with them in the last one. This is the single thing clients tell us they notice first.
We write down what we are not doing.
Every engagement starts with a scope that names the things we have deliberately excluded and why. It makes the first conversation harder and every conversation after it easier.
We stay past the point it is comfortable.
Most firms hand over when the design is agreed and the change has been announced — the moment of maximum fragility. We hand over to named owners after it is running, and we come back to check.
Where this lands
The industries we bring AI & Engineering to.
Related thinking
What we have published on this.
Research
Interoperability isn't a compliance deadline. It's a business model.
CMS-0057-F is being treated as a date to survive. The organizations treating it as an operating decision are the ones still compounding on it in three years.
ResearchWhy transformation programmes stall at month nine
WorkBack-office migration across three delivery centres
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