Grid and historian signal fabric
SCADA-adjacent exports, EMS/DMS context, historian trends, alarm logs, substation events, telemetry snapshots, safe operating limits, and read-only operational records.
Energy & Utilities Agentic OS Control Plane
Utility AI agents that turn grid objectives into governed advisory execution
VDF.AI sits above the grid, asset, outage, field, customer, market, and compliance systems energy teams already run. It coordinates agents for predictive maintenance, outage summaries, field knowledge, SOP drafting, regulatory reporting, customer operations, and market analysis. Read-only. Air-gapped capable. No path to control-system commands. Every action traceable.
8Grid, outage, asset, field, market, and compliance workflows
0Commands sent to SCADA, EMS, DMS, PLC, or plant controls
100%On-premise, segmented, sovereign-cloud, or air-gapped execution
EverySource, retrieval, model route, approval, and output logged
Built for utility control and resilience
NIS2 NERC CIP IEC 62443 EU AI Act GDPR Air-gapped Read-only Human-in-the-loop
Energy control plane
Operational intelligence in. Utility control plane. Evidence out.
Historian exports, OMS events, asset records, GIS layers, market signals, field notes, customer context, regulatory obligations, and engineering knowledge stay where they are. VDF.AI reads approved context, applies OT-boundary and compliance gates, activates the right agents and tools, and returns advisory execution with evidence.
Live advisory execution
Energy & Utilities Agentic OS Control Plane
VDF.AI · energy · model agnostic · sovereign cloud · air-gapped capable · any LLM
01 Intelligence in 02 Control plane 03 Agents & tools 04 Evidence out
Intelligence in
Asset, EAM and field work fabric
EAM, CMMS, inspection notes, work orders, asset health, maintenance history, transformer records, parts data, vendor manuals, and field crew reports.
Outage, OMS, GIS and customer fabric
OMS events, GIS network context, call-center notes, smart-meter signals, restoration updates, customer impact, crew assignment data, and service commitments.
Market, forecasting and demand fabric
Load forecasts, generation availability, tariff rules, demand-response programs, market prices, weather feeds, imbalance signals, and customer program data.
Regulatory, safety and evidence fabric
NIS2, NERC CIP, IEC 62443, environmental filings, safety procedures, regulator correspondence, audit findings, training records, and control evidence.
Utility objective intake
Set the target: reduce outage reporting time, prioritize asset maintenance, find field procedures faster, prepare NERC or NIS2 evidence, improve customer response, or synthesize market risk.
OT boundary, safety and compliance gates
Enforce read-only mode, Purdue boundary separation, role and zone permissions, approved sources, model routing, human review, safety escalation, and no-control-command policies before agents execute.
Utility goal to advisory execution plan
The platform ranks actions by service impact, safety context, asset criticality, customer impact, market exposure, compliance deadline, evidence quality, zone policy, and required human approval.
Grid operations and outage pod
Correlates outage events, alarms, GIS context, call notes, field updates, and crew records to assemble timelines and restoration briefs.
Asset reliability and field pod
Surfaces procedures, asset histories, fault context, inspection patterns, likely maintenance drivers, and cited answers for engineers and crews.
Compliance and evidence pod
Maps NIS2, NERC CIP, IEC 62443, safety, environmental, and market obligations to evidence, reviewers, deadlines, and report outputs.
Customer, market and planning pod
Grounds customer responses, connection queries, demand-response briefs, tariff analysis, forecasting summaries, and planning memos in approved data.
Sovereign utility execution fabric
Runs on-premise, private cloud, sovereign cloud, segmented OT-adjacent environments, or air-gapped enclaves with approved models and governed read-only tool access.
Audit ledger and operations memory
Stores objective, source, retrieval, anomaly, recommendation, model route, reviewer, output, disposition, and lessons learned for future operations and audits.
Evidence out
Outages summarized
Events, field notes, customer impact, root-cause context, restoration actions, and post-incident reports assembled.
Maintenance prioritized
Asset health, anomaly signals, inspection history, parts context, and work-order evidence ranked for human decision.
Field answers cited
Procedures, manuals, P&IDs, safety guidance, and asset records retrieved with source citations and access controls.
SOPs updated
Procedures drafted from approved material, routed to SMEs, versioned, and retained with approval trace.
Compliance packs assembled
Obligations, control evidence, incident records, model logs, reviewer sign-off, and regulator-ready PDFs compiled.
Customers and markets briefed
Customer updates, program answers, tariff context, demand-response summaries, and market-risk briefs drafted with evidence.
How energy and utilities operations transform
From grid, asset, customer, or compliance objective to governed advisory execution
VDF.AI starts with the operating outcome, then coordinates agents, read-only tools, approvals, and evidence so utility teams move faster without weakening the OT boundary.
- 1
Your utility stack stays. The control plane sits above it.
Connect approved read-only context from SCADA-adjacent exports, historians, EMS, DMS, OMS, EAM, CMMS, GIS, CIS, billing, market, security, document, and compliance systems without changing control infrastructure.
Zero rip-and-replace - 2
State the grid, asset, customer, or compliance objective.
Reduce outage reporting from days to hours, prioritize high-risk assets, answer field questions in seconds, close NERC evidence gaps, draft customer updates, or synthesize demand and market risk.
Objective-first execution - 3
Agents activate inside read-only autonomy boundaries.
Outage, reliability, field knowledge, compliance, market, customer, and procedure agents call only approved tools with zone, role, safety, source, model, and human-approval policies enforced.
Advisory by design - 4
Every output returns with evidence and reusable learning.
The platform records sources, retrievals, anomalies, recommendations, model routes, approvals, outputs, and outcomes while building institutional memory for operations, field teams, and auditors.
Auditable at execution
The Energy & Utilities Challenge
Utilities do not need unsafe automation. They need an advisory operating layer.
Energy operators face outage pressure, aging assets, field knowledge loss, complex regulatory evidence, customer expectations, market volatility, and hard OT boundaries. AI must improve decision support without becoming a new operational risk.
01
Operational context is scattered
Historian data, OMS events, asset records, GIS layers, work orders, customer impact, market signals, procedures, and compliance evidence live across separate systems.
02
The OT boundary is non-negotiable
AI must not become a write path into grid or plant controls. Utility teams need read-only, advisory execution with clear separation from SCADA, EMS, DMS, substations, and safety systems.
03
Outage and compliance clocks move fast
Restoration updates, post-incident reports, NIS2 notifications, NERC evidence, safety reviews, and regulator questions require speed and precision when teams are already stretched.
04
Expert knowledge is leaving the field
Procedures age, asset quirks sit in field notes, senior engineers retire, and lessons from incidents disappear unless the system captures and reuses them.
The VDF AI Solution
A utility control plane that governs agents by zone, role, workflow, safety risk, and objective
No migration
Keep SCADA, EMS, OMS, EAM, CMMS, GIS, customer, market, and compliance systems in place
The agentic layer connects approved read-only context.
VDF.AI connects to operational records, historian exports, engineering documents, asset systems, outage systems, customer platforms, market data, risk registers, and compliance repositories through governed tools. Data stays inside your perimeter; agents receive only the scoped access needed for the objective.
Utility control infrastructure should not be disrupted to adopt AI. A governed advisory layer starts with read-only workflows and expands across the operating model.
0
Control-System Changes Required
Advisory layer above existing utility systems
SCADA read-onlyOMSEAMGIS
Objective engine
Start with the utility outcome, not a disconnected automation task
The plan is ranked by service impact, safety, risk, deadline, and evidence quality.
Examples of objective-first utility execution:
- Outage operations: assemble timelines, customer impact, crew context, and post-incident reports
- Asset reliability: prioritize maintenance from historian, condition, inspection, and work-order signals
- Field knowledge: answer procedure and asset questions from approved engineering sources with citations
- Compliance: compile NIS2, NERC CIP, IEC 62443, safety, and environmental evidence packs
- Customer and market operations: ground responses, demand-response analysis, tariff context, and market briefs in controlled data
Goal
To Advisory Plan
Grid · asset · field · customer · compliance
Ranked actionsBoundary gatesEvidence path
Advisory autonomy
Autonomy is constrained by operational risk and system boundary
Each workflow gets the authority level it deserves.
VDF.AI lets operations, engineering, compliance, customer, market, and security leaders define autonomy at the workflow level:
- Assistive: switching-adjacent, safety, dispatch, restoration, market, and regulator-facing decisions stay with named humans
- Delegated: log summarization, evidence gathering, procedure retrieval, field Q&A, and report drafting execute under policy
- Autonomous: low-risk document routing, internal summaries, knowledge retrieval, and approved status drafts can run within thresholds
- Escalated: severe incidents, safety risk, control ambiguity, market exposure, missing evidence, and regulator outputs route to accountable reviewers
- Measured: each workflow reports response time, evidence completeness, exception rates, review status, and audit trail quality
Read-only
Advisory by Boundary
Assistive · delegated · escalated
No OT commandsApprovalsAudit
Where it pays back
Energy and utilities workflows ready for governed advisory agents
VDF AI Agents & Tools
Improve utility workflows with agent-tool networks
Each workflow combines a defined advisory-agent pattern with tools that retrieve evidence, enforce permissions, summarize operational data, verify sources, request approval, generate records, and export the audit trail.
Engineer reviewed
Predictive Maintenance Network
Correlates historian, condition, inspection, and work-order data to prioritize assets and likely failure drivers.
CSVAnomalyRAG
Explore workflow
Operations controlled Outage & Incident Network
Builds event timelines, restoration summaries, impact context, root-cause hypotheses, and response records.
CSVReportDocs
Explore workflow
SME approved Procedure & SOP Network
Drafts switching, field, safety, maintenance, and compliance procedures from approved source material.
DocsApprovalTrace
Explore workflow
Role-scoped answers Field & Engineering Knowledge Network
Answers questions from manuals, drawings, P&IDs, asset records, safety notes, and maintenance history with citations.
RAGOCRCitations
Explore workflow
Reviewer controlled Regulatory Reporting Network
Maps obligations to evidence, drafts compliance reports, and preserves reviewer sign-off for regulators.
CrawlerPDFAudit
Explore workflow
Customer-safe drafting Customer & Market Operations Network
Grounds customer responses, tariff answers, connection processes, demand-response briefs, and market memos.
RAGEmailSheets
Explore workflow
Data-governed retrieval Utility Data Governance Network
Unifies governed retrieval across asset, document, telemetry, customer, market, and compliance data surfaces.
PermissionAuditSources
Explore workflow
Analyst reviewed Threat & Advisory Network
Ingests advisories and internal signals, maps relevance to utility assets, and drafts action-ready briefs.
WebAnomalyCitations
Explore workflow
Under the hood
Technical specifications for energy and utilities advisory execution
| Requirement | VDF AI Capability |
|---|---|
| Deployment model | On-premise, private cloud, sovereign cloud, segmented utility environment, disconnected site, or fully air-gapped deployment options |
| Control-system boundary | Advisory layer on approved read-only data surfaces; no commands to SCADA, EMS, DMS, PLCs, IEDs, substations, plants, or safety systems |
| Data sovereignty | Models, embeddings, prompts, historian extracts, engineering documents, asset records, customer data, compliance evidence, tool calls, logs, and outputs remain inside your perimeter |
| System posture | Overlay architecture above SCADA-adjacent exports, historians, EMS, DMS, OMS, EAM, CMMS, GIS, CIS, MDM, billing, market, security, document, and compliance systems |
| Private RAG | Manuals, P&IDs, drawings, switching procedures, SOPs, maintenance history, field notes, tariff rules, regulatory evidence, and prior decisions stay in governed vector indexes |
| Role-based access | Agents, tools, knowledge, and outputs scoped by operations, engineering, field, customer, market, compliance, security, region, asset class, zone, and role |
| Model routing | Policy-aware routing by data class, workflow risk, safety adjacency, document complexity, confidence need, latency, cost, and approved model inventory |
| Autonomy controls | Assistive, delegated, autonomous, and escalated modes configured by operational risk, safety context, customer impact, market exposure, compliance deadline, and approval policy |
| Audit logs | Immutable logs for objective, source data, retrieval, anomaly signals, tool calls, model route, policy checks, approval, output, and disposition |
| Integration examples | Historian exports, EAM/CMMS, OMS, GIS, CIS, MDM, billing, data warehouse, SIEM, GRC, document stores, field service, market systems, and regulatory repositories |
| Encryption | At-rest and in-transit encryption, customer-managed keys, deployment-specific key separation, and SIEM export |
| Operations | High-availability clustering, backup and restore, offline update packages, health monitoring, long-term evidence retention, and local model operations |
Outcome Snapshot
What changes after rollout
Minutes
To retrieve cited field procedures and asset context from approved sources
Faster
Outage, incident, maintenance, and compliance report preparation
Trace
Every source, anomaly, recommendation, model route, approval, and generated output
Capture
Operations, field, compliance, and asset knowledge as reusable institutional memory
EXECUTIVE BRIEF · CRITICAL INFRASTRUCTURE & ENERGY
OT-segmented & air-gappedOT/IT segmentation safeCritical priority
AI for operations that can't depend on the public cloud
Energy and critical-infrastructure operators run essential services under NIS2 and strict OT security constraints. On-premises and network-isolated AI agents bring modern assistance to engineering and operations without introducing external dependencies.
For operators' CIOs, CISOs, OT security leaders, and heads of engineering and operations.
- Engineering knowledge assistantPrivate retrieval over manuals, procedures, and maintenance history gives engineers grounded, cited answers — capturing retiring expertise.
- Maintenance and work-order supportAgents draft work orders and summarize asset history from internal systems, speeding planning under audit.
- Incident and procedure guidanceAgents surface the right procedures and prior incidents from internal sources during response, inside the perimeter.
A strategic procurement brief for regulated critical infrastructure & energy environments.
NIS2-aligned, network-isolated AI for essential services.
FAQ
Questions energy and utilities teams ask
Does VDF.AI replace SCADA, EMS, DMS, OMS, EAM, CMMS, GIS, billing, or market systems?
No. VDF.AI sits above utility operations, asset, engineering, outage, customer, market, security, and compliance systems as an advisory control plane. Your SCADA, EMS, DMS, OMS, historians, EAM, CMMS, GIS, CIS, MDM, billing, market, document, and compliance platforms remain the systems of record. VDF.AI coordinates agents and tools across approved read-only data surfaces.
Can VDF.AI run behind the OT boundary or in an air-gapped environment?
Yes. VDF.AI can run on-premise, in a private cloud, sovereign cloud, segmented utility environment, or fully air-gapped enclave. Models, embeddings, prompts, operational records, engineering documents, asset context, tool calls, and audit logs remain inside your controlled perimeter with no unmanaged external runtime calls.
Will VDF.AI issue commands to grid or plant control systems?
No. VDF.AI is advisory by design. It can retrieve procedures, summarize logs, correlate alarms, draft reports, prepare recommendations, and route work for approval, but it does not write to SCADA, EMS, DMS, PLCs, IEDs, substations, plants, or other control systems. Operators, engineers, and field supervisors retain authority for switching, dispatch, safety, restoration, and control decisions.
How does VDF.AI support NIS2, NERC CIP, IEC 62443, EU AI Act, and regulator evidence?
Agents can map obligations to controls, retrieve approved evidence, monitor regulatory change, summarize incident timelines, draft notifications, compile compliance packs, and preserve the full review trail. Every source, retrieval, model route, recommendation, approval, and output is logged so utility teams can defend the record.
Build the utility control plane above the systems you already trust
Start with one objective: outage reporting, field knowledge, predictive maintenance, SOP drafting, regulatory evidence, customer operations, market analysis, or threat advisory synthesis.