Process
From one painful workflow to a working AI pilot.
The process starts with discovery, moves into a focused demo, then becomes an integrated workflow only if the pilot proves useful. You see what is being built, why it matters, and what improves next.
Process
Start with one workflow. Prove value before scaling.
search01
Map the pain point
Understand the workflow, the people involved, the data, and the cost of the current friction.
science02
Build the pilot
Create a focused AI demo or workflow around one practical use case, then test it with real scenarios.
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Deploy and optimise
Connect the system to your tools, train the team, monitor usage, and improve it monthly.
Review Output
Discovery is useful even before anything gets built.
- search_checkWhich workflow is slow, repetitive, expensive, or hard to scale
- search_checkWhat systems, documents, messages, and data the workflow depends on
- search_checkWhere AI can safely assist and where a human must stay in control
- search_checkWhat the smallest useful pilot should prove before a larger rollout
Typical Timeline
Clear stages, visible demos, and no technical fog.
- task_altWeek 1: discovery calls, workflow map, data access, and pilot definition
- task_altWeeks 2-3: prototype, prompts, automations, integrations, and test cases
- task_altWeeks 4-6: rollout, team feedback, edge-case handling, and reporting baseline
- task_altMonthly: monitoring, workflow updates, new use cases, and system improvements
Next Step
Start with the bottleneck, then decide what is worth building.
No pressure to automate everything at once. The first conversation identifies the highest-leverage workflow so the pilot stays small, useful, and testable.