Tailored AI Solutions

Where does AI actually pay in a company like mine?

Two to three weeks of walking your real processes, then a ranked list of use cases with the numbers behind each one and the order to build them in.

• 2 to 3 weeks from kickoff to a decision
• 4 to 6 interviews with your team
• One half day workshop
• No licences and nothing to buy

1. Process inventory. We walk the work as it is done, not as the process map says it is done. Volumes, handoffs, the spreadsheet everyone maintains privately, the approval that adds four days.
2. Ranked use cases. Every candidate scored on value and on feasibility, including the ones we recommend against. A short honest list beats a long flattering one.
3. The numbers behind each one. Hours today, hours after, build cost and payback, derived from your volumes and your rates rather than from an industry benchmark.
4. Build sequence. The order to build in, and the reasoning. The first one has to be small enough to finish and visible enough to matter.

Will my own people be able to run this once you leave?

Role by role training on your processes and your data, run as cohorts, ending with people who build and fix the workflows themselves.

• Cohorts of 8 to 12 people
• Half day sessions over 4 to 6 weeks
• Built on your processes, not on generic examples
• Handbook and recordings stay with you

1. Baseline and roles. Who has to operate it, who has to build it, who only has to review it. Three different courses, not one deck shown three times.
2. Working sessions. People bring their own tasks. Every session ends with something that runs on Monday, because a course with no artefact is forgotten in a fortnight.
3. Build track for owners. The two or three people who will own the workflows go deeper: prompts, evaluation, and the point at which you stop trusting a model and escalate.
4. Handbook and handover. Materials your own people can teach from, so competence does not stay concentrated in whoever happened to be in the pilot.

Who actually builds it, and how long until it runs by itself?

End to end delivery from the first pilot to production: the workflows built, wired into the systems your teams already use, and watched until they run without being asked.

• First workflow live in 6 to 8 weeks
• One process end to end, never five at once
• Wired into the systems you already run
• Documented handover, no lock-in

1. Pilot on one process. One process, end to end, with a number attached. A pilot that touches five processes proves nothing about any of them.
2. Integration. Into the systems your teams open every morning. A workflow that lives in a separate browser tab is a workflow nobody uses by March.
3. Production hardening. Failure paths, escalation, logging and the boring part: what happens on the day the model answers badly.
4. Handover. Runbooks, owners and the access to change it yourselves. We leave the keys, not a dependency.

How do I keep this alive and measurable after go-live?

The layer that holds every workflow, prompt and output in one place, owned by you, measurable from the first week. Currently in private preview.

• One place for every workflow and prompt
• Usage and output quality visible weekly
• Your data stays in your own tenant
• In private preview with pilot clients

1. One catalogue. Every workflow the company runs, with its owner, its cost and the date it last changed. The alternative is prompts living in private chats.
2. Measurement from week one. Usage, output quality and hours saved, tracked per workflow, so the business case survives contact with the second quarter.
3. Governance without a committee. Access, retention and review built into the workflow rather than into a policy nobody reads.
4. Export and exit. Every prompt, workflow and log is exportable from day one. A platform you cannot leave is a platform you cannot trust with the work that matters.