Scope
Select transformer population, evidence streams, decision workflow, and pilot owners.
Pilot evaluation
Prove the workflow before broad deployment
A GridAPM Ai pilot helps transformer teams test whether agentic AI can turn approved evidence into human-reviewed APM decisions with stronger traceability, lifecycle context, and sustainability relevance.
Pilot path
Five steps from scope to evidence pack
The pilot should remain focused: one transformer population, known evidence streams, clear review owners, defined security boundaries, and practical success metrics.
Prepare
Collect approved records, align asset identifiers, and define review and data boundaries.
Analyze
Run the GridAPM evidence model, agent workflow, health index review, and lifecycle context mapping.
Review
Engineers inspect AI rationale, uncertainty notes, recommendations, and evidence links.
Report
Deliver a pilot evidence pack, decision log, value summary, and next-step plan.
Success metrics
Measure decision quality, not hype
Early evaluation should focus on preparation time, evidence completeness, review clarity, traceability, and usefulness for lifecycle and sustainability planning.
Diagnostic review preparation time
Completeness of evidence record
Clarity of health index drivers
Traceability from recommendation to source data
Engineer confidence in review workflow
Usefulness for lifecycle and sustainability planning
Deliverables
Procurement-ready proof assets
The goal is to give engineering and asset leaders something they can inspect, discuss, and compare against current review processes.
Pilot evidence model
A structured view of transformer records, source provenance, diagnostic streams, and asset context.
Decision workflow map
A practical map of how evidence moves from ingestion to engineer-reviewed action.
Sample evidence pack
A review-ready report showing condition evidence, AI rationale, lifecycle context, signoff, and next actions.
Value framework
A conservative summary of time, traceability, review quality, lifecycle, and sustainability value hypotheses.
Pilot FAQ
Questions before the first evaluation
How many transformers should a pilot include?
A focused first pilot can start with a small population where historical evidence exists and the team has a clear review workflow to evaluate.
Do we need live integrations for a pilot?
No. A pilot can begin with approved historical records and controlled datasets. Live integrations can be evaluated after the workflow proves useful.
What should GridAPM not claim in a pilot?
The pilot should avoid unsupported claims about guaranteed failure prevention, autonomous control, or quantified performance until real evidence supports those claims.