Diagnostic
Determine whether one workflow is valuable, measurable and controllable enough to justify a pilot.
State Method Diagnostic / construction AI workflows
€4,000 excluding VAT · 10 business days · One workflow
State Method checks the evidence, permissions and recovery path for one proposed workflow. Get five decision artifacts and a reasoned build, change or stop recommendation. No obligation to pilot.
Approval remains human-owned
Entry points / three construction tasks
These illustrative synthetic examples show where a controlled AI workflow could begin. They are not client deployments, products or measured results.
A product submittal must be checked against an approved specification section before it can be accepted.
Approved specification sections and product evidence → Approved compliance matrix with exceptions
Approval owner / Technical Manager
Explore Specification Compliance Review →Requests arrive across several channels and are re-keyed into the project register by hand.
RFI or submittal email, form and attachments → Approved intake record and assigned review route
Approval owner / Project Coordinator
Explore RFI & Submittal Intake →Site notes, photos and video are matched to observations and written up after the visit.
Authorized site notes, photos, video and reporting period → Approved progress report with linked evidence
Approval owner / Site Manager
Explore Site Progress Reporting →Problem / control gap
A plausible model output is not enough. The surrounding workflow also needs an explicit state, defined permissions, validation, a human approval owner, observable failure and a recovery path.
Ambiguous / unbounded
Controlled / observable
The workflow exposes where each case is.
Tools act only inside defined permissions.
A named person approves consequential outputs.
Failure stops, logs and routes for review.
Protocol / five states
The method turns one operational workflow into a bounded system whose evidence, authority and failure paths can be inspected.
Apply it to one workflowDefine exactly where the workflow starts, where it ends and who remains responsible for its outcome.
Test the workflow on evidence that resembles real operating conditions.
Decide what the model may propose, what software must enforce and what a person must approve.
Make failure visible and recoverable before the workflow can affect real operations.
Use the evidence to choose the next controlled step instead of assuming every prototype deserves production.
Commercial path
Diagnostic → Controlled Pilot → Production System is a decision path, not a guaranteed funnel. A valid outcome can be to change the design, gather better data, keep the workflow manual or stop.
Determine whether one workflow is valuable, measurable and controllable enough to justify a pilot.
Build the smallest useful version with real tools, representative cases and explicit controls.
Harden integrations, reliability and ownership only when the evidence supports it.
Controlled pilot / evidence in use
The pilot uses real tools and representative cases to test whether the proposed workflow works under controlled conditions. It is a bounded implementation, not an open-ended production build.
A pilot does not guarantee production readiness. The result is an evidence-backed go, change or stop decision.
Discuss a controlled pilotFixed-scope diagnostic
The diagnostic determines whether one AI-assisted workflow is valuable, measurable and controllable enough to justify a pilot. It is a decision engagement, not a small production implementation.
Artifacts delivered
What happens next
You receive a proceed, change, gather-more-evidence or stop recommendation. A controlled pilot specification is included only when justified.
Historical client work
Hugo Sequier contributed engineering to these client projects before State Method launched. They are not State Method products or companies owned by Hugo. Results belong to their original context.
An AI system connecting document reading, floorplan analysis, verification actions and a review interface.
A production pipeline for PDF intake, polygon extraction, post-processing, rule-based checks and reporting.
A video pipeline that segments uploads, extracts report evidence and prepares a structured draft for office review.
Qualification boundary
→Good fit
×Outside the method
Founder-led engineering
Hugo is an AI engineer and data scientist with seven years in software development and production experience across AI agents, document intelligence, computer vision and full-stack systems.
View Hugo’s workWorkflow assessment / first step
Describe the construction process today, the documents or project evidence involved, what the agent should produce, who reviews it and the current volume or baseline.