Enterprise utilities operational intelligence. Not dashboards.
Governed outage intelligence, asset observability frameworks, infrastructure monitoring, and operational KPI platforms — engineered by Unolabs so water, energy, and utility operators act on live grid and field signals instead of lagged reports.
SCADA, GIS, AMI, OMS
Operational telemetry + real-time infrastructure signals
UTILITY DOMAIN INTELLIGENCE
Outage orchestration + asset observability
OPERATIONS, COMPLIANCE, AUTONOMY
Operational intelligence + automated response systems
What is Utilities Intelligence Accelerator?
A utilities intelligence accelerator is a pre-built set of governed data domains, KPI definitions, and analytics models for grid and field operations — asset, outage, customer, and crew entities aligned to how SCADA, GIS, AMI, and OMS estates actually describe the network. Instead of modelling the utility from scratch, teams configure proven domain templates, landing a first operational release in 10–14 weeks with regulatory reporting lineage designed in from the start.
One operational truth across SCADA, GIS, AMI
Your control room, field crews, and regulators each see a different version of the network, and every outage replays the reconciliation. The utilities accelerator lands governed asset, outage, and KPI domains in a 10-14 week first release — with the compliance lineage regulators ask for designed in rather than assembled afterwards. Operational systems stay untouched; the intelligence layer unifies them.
Why utilities transformation initiatives fail
Fragmented Operational Systems
SCADA, GIS, AMI, outage management, work management, and billing systems operate without a unified operational intelligence layer, preventing cross-domain decisions.
Disconnected Infrastructure Intelligence
Asset health, outage events, weather signals, and crew availability exist in isolated systems with no joined operational context for prioritisation or response.
Siloed Field Operations
Field crews and control room operators operate from different data sources, creating misalignment during outage events and maintenance cycles.
Weak Observability Frameworks
Absence of real-time operational cockpits means utility leadership makes decisions on stale, aggregated reporting rather than live infrastructure intelligence.
Delayed Incident Response
Without automated outage impact scoring and restoration prioritisation, operations teams lose critical response time coordinating across disconnected platforms.
Poor Governance Standardisation
Without governed KPI taxonomies and data stewardship models, operational teams report conflicting metrics and waste cycles reconciling regulatory evidence.
Business Outcomes Enabled by Utilities Operational Intelligence
Faster Operational Decision-Making
Enable infrastructure operators and field teams to act on live outage, asset, and grid signals rather than lagged operational reports.
Improved Infrastructure Visibility
Eliminate blind spots across SCADA, GIS, AMI, and outage management systems with a unified operational intelligence layer.
Reduced Operational Downtime
Shift from reactive outage response to predictive asset health monitoring and proactive maintenance prioritisation.
Enhanced Field Operations Intelligence
Equip crews with real-time work order intelligence, asset criticality context, and restoration prioritisation frameworks.
Improved Operational Resilience
Build infrastructure observability ecosystems that sustain operational continuity during outage events and grid stress scenarios.
Regulatory Readiness
Establish governed reporting lineage for service quality, reliability, billing, and compliance evidence without manual assembly.
How Utilities Intelligence Accelerator delivery works
The view below shows how work moves through the delivery flow — from inputs, through governed controls, to operational outputs.
Utility Operational Intelligence Data Flow
Source Layer
SCADA, GIS, AMI, OMS
Grid, asset, and customer-facing systems emit meter, outage, location, and service events via SCADA and AMI connectors on Azure and Databricks.
Engineering Layer
Governed Utility Intelligence Domains
Asset, grid, outage, customer, crew, and billing domains are standardised into governed enterprise utility intelligence templates.
Outage, Asset & Grid Features
Features support outage impact scoring, asset health monitoring, restoration prioritisation, crew dispatching, and regulatory evidence.
Activation Layer
Operations, Compliance, Agents
Control room operators, field crews, regulatory teams, and autonomous agents receive prioritised actions via Power BI, MS Fabric, and operational cockpits.
SCADA, GIS, AMI, OMS
Governed Utility Intelligence Domains -> Outage, Asset & Grid Features
Operations, Compliance, Agents
Field Signals -> Domain Model -> Intelligence -> Action
Access
Identity, RBAC, purpose, and least privilege.
Quality
Freshness, completeness, validity, and anomaly checks.
Lineage
Source, transformation, owner, and consumer traceability.
Operations
Monitoring, retry, alerting, runbooks, and evidence.
How Unolabs engineers Utilities Intelligence Accelerator
Utility Domain Model Fit
We map your asset, grid, customer, premise, outage, crew, work order, and billing entities to governed, reusable utility intelligence templates on Azure, Databricks, and Snowflake.
Operational Signal Integration
We combine SCADA, GIS, AMI, outage management, work management, weather, and customer systems into standardised intelligence layers powered by Power BI and MS Fabric.
Asset Observability
We build asset health indicators, failure risk scores, maintenance criticality rankings, and infrastructure performance signals for field and control room teams.
Outage Intelligence Architecture
We connect event signals, asset history, weather context, crew availability, and customer impact into a unified outage intelligence and restoration prioritisation framework.
Semantic BI Layer
We define governed measures for outage frequency, restoration time, asset reliability, service quality, and compliance metrics across Power BI and MS Fabric environments.
Operational KPI Governance
We establish standardised KPI taxonomies and data stewardship models that eliminate conflicting operational reporting across functions and regulatory teams.
Enterprise Utilities Intelligence Maturity Model
Where does your organisation sit on the path to autonomous operations? Use this model to identify your current stage and the critical engineering gaps preventing progression.
Fragmented operational reporting
Isolated, manually assembled operational reports from SCADA, GIS, and billing with no unified infrastructure intelligence or standardised KPI definitions.
Department-level infrastructure analytics
Asset and outage analytics exist but remain siloed, with limited cross-domain operational visibility or joined intelligence between field and control room.
Governed enterprise utility intelligence
Standardised asset, outage, and operational KPI models with governed taxonomy and cross-functional infrastructure observability.
Real-time operational observability
Live grid, asset, and outage signals power operational decisions across control rooms, field crews, and regulatory reporting teams.
Autonomous utility intelligence ecosystems
Agentic infrastructure orchestration and self-optimising operational intelligence that adapts to real-time grid and field signals.
Industry Benchmarking
Transformation Progression
Utility Intelligence Audit
Assessment of current operational data estate, outage signal coverage, asset data gaps, and infrastructure observability maturity.
Architecture Design
Designing the enterprise utility domain model, outage intelligence layer, and infrastructure observability framework.
Domain Model Deployment
Deploying standardised asset, grid, outage, customer, crew, and billing domains with governed KPI definitions.
Intelligence Activation
Publishing outage analytics features, asset health scores, and infrastructure performance cockpits for operational teams.
Autonomous Utility Operations
Enabling agentic infrastructure orchestration, automated maintenance signals, and self-optimising operational intelligence workflows.
Utilities Operational Intelligence Use Cases
Automated outage impact scoring, restoration prioritisation, and crew dispatch intelligence
Real-time asset health monitoring, failure risk scoring, and maintenance prioritisation frameworks
Governed utility KPI taxonomy across reliability, service quality, and compliance reporting
Work order context, crew availability, and field asset intelligence for operational teams
SCADA, GIS, and AMI signal integration for transformer, feeder, and grid asset observability
Governed lineage and reporting marts for reliability, service quality, and billing compliance evidence
What this means in practice
Operational Context Requires an Asset Graph
Utility intelligence depends on traversable relationships — which meters hang off which transformer, which feeder an outage isolates, which crew holds the nearest switching context. The accelerator builds that graph from GIS connectivity and asset history, reconciling the as-built network with the as-operated one so impact scoring and restoration prioritisation reflect the grid as it actually runs.
From Reporting to Orchestration
The same governed data products power outage dashboards, field crew alerts, and asset maintenance signals — and, where utilities operate ADMS or DERMS, the analytical context those systems consume. One intelligence layer feeds human decisions and agentic workflows alike, so orchestration becomes an extension of the estate rather than a parallel build.
Regulation Is Designed In
Reliability marts carry lineage from OMS event to filed SAIDI/SAIFI number, exclusion logic is codified rather than analyst-dependent, and retention schedules match filing cycles. Compliance evidence becomes a by-product of daily operation — not a manual assembly exercise before each reliability or rate submission.
Utility Operational Intelligence Data Flow
The utility intelligence flow shows how field, grid, asset, and customer signals converge into governed outage, asset, and infrastructure intelligence ecosystems.
SCADA, GIS, AMI, OMS
Grid, asset, and customer-facing systems emit meter, outage, location, and service events via SCADA and AMI connectors on Azure and Databricks.
Governed Utility Intelligence Domains
Asset, grid, outage, customer, crew, and billing domains are standardised into governed enterprise utility intelligence templates.
Outage, Asset & Grid Features
Features support outage impact scoring, asset health monitoring, restoration prioritisation, crew dispatching, and regulatory evidence.
Operations, Compliance, Agents
Control room operators, field crews, regulatory teams, and autonomous agents receive prioritised actions via Power BI, MS Fabric, and operational cockpits.
Utilities Intelligence Accelerator: from input to operational asset
The flowchart turns the service into a delivery sequence so buyers can see the real work, not just the promise.
Business Input
Faster Operational Decision-Making
Architecture Decision
Utility Domain Model Fit
Data Treatment
Governed Utility Intelligence Domains
Controls Applied
Outage, Asset & Grid Features
Operational Output
Operations, Compliance, Agents
Visible work products, not vague advice
Each deliverable is designed to be used by executives, architects, engineers, data owners, and operations teams after the engagement ends.
The delivery path
Discover
Audit operational data estate, outage signal coverage, asset data gaps, regulatory reporting conflicts, and infrastructure observability maturity.
Design
Define the enterprise utility domain model, governance taxonomy, outage intelligence architecture, and infrastructure observability framework.
Build
Deploy governed domain templates, asset health features, outage analytics, and operational dashboards across Azure, Databricks, Snowflake, and Power BI.
Scale
Expand the utility intelligence architecture across new grids, asset classes, and operational regions through configuration rather than custom engineering.
What changes after the work
Faster operational decision-making
Improved infrastructure visibility
Reduced operational downtime
Better outage response coordination
Improved asset monitoring
Increased operational resilience
Enhanced field operations intelligence
Faster regulatory compliance readiness
Frequently Asked Questions
How do you get OT data out without widening the CIP perimeter?
Through one-way, outbound-only replication: historian and SCADA-derived data is mirrored into a collection tier in the CIP DMZ, and the analytics platform reads from that tier on the corporate side. No inbound connections into the electronic security perimeter are created, no analytics tooling is installed on OT assets, and the existing CIP asset scope is left unchanged — the accelerator consumes only what the boundary already permits to flow outward.
Do you integrate with our existing ADMS, OMS, and GIS?
Yes — the accelerator reads from them rather than replacing them. Outage events come from OMS, network topology and connectivity from GIS, and switching or state context from ADMS where an interface exists. Domains are aligned to IEC CIM (61968/61970), which keeps those mappings stable across vendor upgrades. Any write-back into operational systems goes through their existing APIs and operator review, never directly from the analytics layer.
How is AMI interval data handled at scale?
Interval reads are extracted from the AMI head-end or MDM — preferring VEE-processed reads so validation and estimation flags survive into analytics. At 15-minute granularity a million meters produce roughly 96 million reads a day, so lakehouse zones are partitioned by meter and read timestamp, late and re-issued reads are versioned rather than overwritten, and multi-year retention is tiered to keep rate-case analysis affordable.
What does the first release include?
A typical 10–14 week first release lands the governed asset, outage, and customer domains; reliability KPI marts computing SAIDI, SAIFI, and CAIDI with codified exclusion logic; asset health and outage-impact scoring; and operational cockpits for control-room and field teams. The week-one scoping audit confirms which domains and source systems make the first cut, based on extract availability and reporting priorities.
How an engagement starts
A 45-minute scoping call with a utilities data lead — bring your outage and asset reporting gaps; leave with a read on template fit and a proposed first-release scope.
Bring your outage reporting gaps. Leave with a scoped first release.
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