Trust & responsible AI

The AI drafts.Your engineer decides.

GridAPM Ai is built for evidence, planning, and reporting workflows where explainability, operational boundaries, and engineering accountability matter. Every recommendation passes a human gate before it becomes an action.

  • Human approval required
  • No autonomous control
  • Local-first pilot datasets
  • Audit-ready decision records

OT boundary

Site network

Workstation

GridAPM

Controlled OpenAI connection

Evidence in

GridAPM is an instrument your engineers run: deployed on their workstation, inside your perimeter, with every decision signed off by a named engineer.

AgenticGrid Pro Transformer APM

The other GridAPM product ProtectionAI Relay testing

Compare both products

Principles

Trust is designed into the workflow

GridAPM Ai makes it easy to review what happened: which evidence was used, which assumptions mattered, and which person approved the next action.

  • Human approval

    AI supports review work. Engineers decide — they approve, reject, or escalate every recommendation.

  • No autonomous control

    GridAPM Ai serves evidence, planning, and reporting workflows — never autonomous transformer control.

  • Traceable evidence

    Recommendations link back to source records, assumptions, uncertainty, and review state.

  • Controlled pilots

    Evaluation begins with approved datasets and local-first workflows, with OpenAI access scoped before any broader integration.

  • Data minimization

    Pilot scope uses only the evidence needed to evaluate the agreed workflow.

  • Reviewable AI

    Agent activity is logged with rationale, inputs, outputs, and the human sign-off that closed it.

The human gate

No autonomous control — every action needs a named engineer

Stage 4 of the pipeline is mandatory. The screen below is the gate itself: approve, edit, reject, or escalate — each decision stamps the audit log.

  1. Intake
  2. Correlate & quality gate
  3. Agent reasoning
  4. Engineer sign-off
  5. Work package & report
GridAPM Workbench — local deployment Synthetic demo data

AI draft — awaiting engineer review

Reviewer: M. Okafor, P.E. · Senior substation engineer

Re-sample oil in 30 days; keep the PD monitor trending on the HV-B bushing; thermographic follow-up on the B-phase LV connection; inspect and re-torque at the next planned outage.

Awaiting engineer decisionNothing ships without a named engineer's decision.

  1. intake · 7 files received, 4 sources correlated
  2. quality gate · passed — 1 correction (IR clock drift)
  3. agent/dga-v2.3 · draft v2 created — confidence 0.78
  • Local-first
  • No OT connection
  • Audit log on
Product screen: engineer sign-off for TX-47 — Approve, Edit, Reject or Escalate; each decision stamps the audit log. Try the buttons: the states are pre-rendered.

Governance model

Who acts, who decides

Every pilot defines four zones before evaluation begins: what agents may do on their own, what they may only draft, what engineers alone decide, and what stays outside the software entirely.

Agent may act

Parsing, normalizing, and aligning approved evidence files; computing trends and quality flags.

Agent may draft

Condition assessments, risk rationale, report language — always labeled as an AI draft awaiting review.

Engineer decides Human gate

Every approval, edit, rejection, and escalation — nothing becomes an action without a named engineer.

Out of scope

Autonomous switching, protection settings, real-time operation, final operational authority — never in the software.

Audit trail

Every decision leaves a mark

The audit boundary is defined up front: the evidence pack, assumptions, reviewer identity, timestamps, and final decision state are preserved. Entries are append-only — edits add to the record, they never rewrite it.

Reviewed Engineer sign-off stamp: Reviewed, initials R.K., dated Mar 12, 2026. Reviewed R.K. Mar 12, 2026
Evidence pack
Source records, assumptions, and uncertainty notes stay attached to every finding.
Reviewer identity
Each decision names the engineer who made it, with their role and comments.
Timestamps
Every state change — draft, edit, approval, escalation — is dated in the log.
Final decision state
The approved, rejected, or escalated outcome closes the record and travels with the report.

Trust FAQ

Questions security and engineering teams ask

Does GridAPM Ai control transformer equipment?

No — by design. GridAPM Ai is human-reviewed decision support: it organizes evidence, drafts reasoning and recommendations, and produces reports. Engineers hold final authority over every action.

Can GridAPM be evaluated offline?

Yes. A pilot is scoped around approved datasets and local-first workflows. OpenAI access and deployment details are reviewed against your security and operational technology requirements.

How does GridAPM handle responsible AI?

Bounded agent tasks, visible evidence, uncertainty notes, human approval, audit trails, and conservative claims — the same principles on this page, applied in the product.

Meet the human gate

See the sign-off workflow on your own evidence — scoped, local-first, engineer-approved.

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