Solutions · Energy & Utilities

Built for the grid.
Not adapted to it.

Most governance platforms learn your asset hierarchy from training materials. Ours was built by people who spent years inside gas and electric utility data before CelesteIQ existed - GIS, EAM/CMMS, SCADA, AMI, and the regulatory filings that depend on all of them agreeing.

⚡ Energy & Utilities Financial Services Coming soon Healthcare Coming soon Manufacturing Coming soon
The utility data problem

Your systems don't agree with each other.

GIS says one thing about an asset. EAM says another. SCADA has a third answer, and the meter data reconciliation report has a fourth. Generic governance tools catalog all four versions. They don't tell you which one is right — or why they drifted apart.

OT/IT Divide

GIS, EAM, SCADA, AMI

Four systems of record for the same physical asset, updated on four different cadences by four different teams. Nobody owns reconciling them.

Asset Hierarchy

Non-standard modeling

Feeders, transformers, meters, and gas mains rarely map cleanly to a horizontal tool's generic table/schema model. Utility asset hierarchies need utility-native object types.

Regulatory Load

NERC CIP · PHMSA · PUC

Grid reliability, gas pipeline safety, and rate case filings all draw on the same underlying data — and all three auditors ask different questions about it.

Silent Decay

Nobody sees drift coming

Critical Data Elements degrade quietly after a source-system migration or field-crew workaround — until the bad number lands in a report, months later.

CDE Decay Modeling

We treat data accuracy
like asset reliability.

Utilities already know how to think about failure: the P-F curve. An asset shows a potential failure signal (P) long before it functionally fails (F) - and that interval is your window to act. We apply the same survival-analysis model to Critical Data Elements.

  • Potential-drift detectionStructural signals - a source migration, a schema change, a spike in manual overrides - flag decay before the number is visibly wrong.
  • The P–F interval, quantifiedEvery CDE gets a modeled decay curve, so stewards know how much runway they have before a field becomes unreliable.
  • Act before the audit doesCatch CDE drift while it's still a data-quality ticket, not a NERC CIP finding or a rate case objection.
CDE Decay Curve — Asset ID: Feeder-2214 Connected Time since last verified 100% Trust P — drift detected CelesteIQ flags the asset F — functional failure P–F interval — CelesteIQ's window to act
Trust score over time Potential drift (P) Functional failure (F)
This is a live governance-graph node, not a one-time score. As new structural signals arrive from GIS, EAM, or SCADA, the curve - and the stewardship priority — updates automatically.
Asset-First Knowledge Graph

One graph, every system of record.

Feeders, transformers, meters, gas mains, and substations are modeled as first-class object types - not rows in a generic table - so lineage, ownership, and quality all resolve to the same physical asset, no matter which system reported it.

  • Utility-native object modelAsset hierarchies built from real utility data models, not retrofitted from a horizontal schema.
  • Cross-system resolutionGIS, EAM/CMMS, SCADA and AMI records for the same asset are linked, not just cataloged side by side.
Asset Graph
[ asset-first knowledge graph view ]
feeders · transformers · meters · gas mains
Predictive Lineage

Lineage before you finish connecting.

Structural signals — naming conventions, join patterns, transform logic - let CelesteIQ predict lineage across OT and IT systems before manual tagging even starts, using the same techniques we built mapping utility data estates by hand for years.

  • Day-one lineage, not day-ninetyPredicted lineage populates the graph immediately on connection; stewards confirm rather than build from scratch.
  • Confidence-scored, not guessedEvery predicted edge carries a confidence score, so you know exactly what still needs a human look.
Lineage Prediction
[ predicted lineage, confidence-scored ]
GIS → EAM → SCADA → reporting
Compliance-Ready Governance

Audit-ready, not audit-scramble.

NERC CIP evidence, PHMSA integrity data, and PUC rate case filings all draw from the same governed graph — so the answer you give one regulator matches the answer you gave the last one, automatically.

  • One source, every filingRegulatory reporting pulls from the governed graph instead of a parallel spreadsheet process.
  • Traceable evidenceEvery CDE used in a compliance filing carries its lineage and quality history for the audit trail.
Compliance View
[ regulatory evidence trail ]
NERC CIP · PHMSA · PUC filings
Frameworks we speak natively

Governance mapped to how you're actually audited.

NERC CIP

Grid reliability and cybersecurity evidence for BES Cyber Systems, tied to the same asset graph you already govern in.

PHMSA

Gas pipeline integrity data — material, inspection, and incident records — reconciled instead of siloed by system.

State PUC filings

Rate case and reliability reporting sourced from governed, lineage-traceable data instead of a parallel export process.

Get Started

Talk to people who've done this on your kind of data.

No generic demo environment. We'll walk through your actual asset hierarchy and show you what CelesteIQ predicts on day one.