Discovery
Frame the business problem in operational terms, map the current context, and define what should be built first.
Methodology
How ARTIFICO Delivers AI and Automation
Discovery to pilot to working layer to scale
ARTIFICO does not treat AI and automation work as a one-step rollout. The work moves through a staged model so the team can define the real problem, prove one useful scenario, turn it into a working layer inside the process, and expand only after the first contour is usable and observable.
Who this process is for
This model fits teams that already see a real process problem but do not want to jump straight into a broad implementation without a clear boundary, ownership model, or quality logic. It is especially useful when the work affects internal operations, customer-facing workflows, or AI and automation scenarios where review and control matter as much as the initial build.
The stage model
Pilot
Make one narrow scenario usable enough to test value, reviewability, and the continue-or-stop decision.
Working Layer
Integrate the solution into a real process with ownership, review logic, and observability.
Scale
Expand in a controlled pattern by adding scenarios, systems, and governance only after the base is working.
Typical artifacts by stage
Discovery
- business problem framing
- system and context map
- source or data inventory
- success criteria
- risk notes
Pilot
- one working scenario
- evaluation logic
- review boundaries
- first usable implementation
- continue, revise, or stop decision
Working Layer
- integrated workflow
- operational ownership
- monitoring or quality loop
- handoff rules
- update logic
Scale
- expansion to new scenarios
- more roles or systems
- broader automation or governance
- controlled rollout pattern
Pilot and working-layer boundaries
Pilot
One narrow scenario with a controlled workflow and an explicit quality or evaluation boundary. The goal is not to promise a full solution but to test whether the implementation is valuable, reviewable, and worth continuing.
Working Layer
This stage begins when the solution is integrated into a real process rather than sitting as an isolated proof point. Review logic and observability stop being optional here.
Where this methodology fits
Best fit
Teams with a visible process problem, a first priority scenario, and a need to define quality, ownership, and rollout logic before expanding.
Poor fit
Teams looking to jump straight into a broad rollout without a clear boundary, review logic, or an agreed first working contour.
Handoff and support
Handoff begins at the working-layer stage, when the solution is already part of a real process.
Support and iteration may continue after launch, but they should be framed as an operating rhythm rather than as an open-ended promise. The exact split between ARTIFICO ownership and client ownership still depends on scope and engagement model.
AI implementation