What we automate
We build AI for energy systems that integrate with the operational reality of Australian energy and utilities businesses. Common workflows we automate end-to-end:
- Asset condition monitoring and failure prediction
- Demand forecasting and load planning
- Outage detection, restoration tracking, and customer notification
- Regulatory reporting (AEMO, AER, state ESCs)
- Customer service automation and bill inquiry handling
- Network capacity planning and DER integration
- Field crew scheduling and dispatch
Built for the realities of energy and utilities
AEMO and AER reporting obligations have specific structured formats.
OT/IT convergence requires careful protocol bridging.
Customer-facing outage communication has reputational stakes.
DER (distributed energy resources) integration is rapidly changing the operational reality.
Why work with us on AI for energy
AI for energy work that respects the AEMO and AER reporting obligations, the OT/IT bridge required for utility operations, and the rapid change DER is bringing to the network.
Where most AI in energy utilities goes wrong
Most AU energy and utilities AI engagements get scoped against a single asset class or a single business function without integrating across the OT layer, the asset management layer, and the customer-facing operations. The fragmented patterns: AI for predictive maintenance without integration to the work-order system; outage management AI that doesn't surface in the customer communication workflow; "AI for demand forecasting" without integration to the market participation systems; AI for field operations that doesn't reach mobile devices in the field; and AI deployed in isolation from the SOCI Act and AEMO obligations. Energy and utilities sit on critical infrastructure with hard regulatory obligations and operational realities that AI must respect.
Systems we integrate against
Energy and utilities AI engagements typically integrate against SAP IS-U for billing and customer information, Oracle Utilities, OSIsoft PI for the OT historian, IBM Maximo for asset management, GE Smallworld for GIS, OMS platforms for outage management, AEMO market participation systems for generators and retailers, SCADA for the OT layer, field-mobility platforms (ClickSoftware, ServicePower), and the various trading and risk platforms. AU utilities typically run a heterogeneous mix with limited IT-OT integration. The integration work, with explicit attention to the OT boundary, is where the value lives.
If your stack isn't listed above, reach out anyway. The systems vary by industry but the integration patterns don't. We can usually work with whatever you're running. Tell us your stack.
Regulatory and compliance landscape
The AU energy and utilities regulatory stack is dense: the SOCI Act with its critical infrastructure obligations and reporting requirements, the National Electricity Rules and National Gas Rules administered by AEMC and enforced by AER, AEMO operational obligations for market participants, state-based water and energy retailer licensing, customer protection obligations under the National Energy Customer Framework, the Privacy Act for customer data, and the cyber security obligations specific to electricity infrastructure. We design AI deployments with explicit attention to the SOCI Act reporting obligations and the AEMO market-conduct requirements where applicable.
Operational outcomes we move
Defensible outcomes we have moved on energy and utilities engagements: outage-management response time reduced; asset condition assessment cycle time compressed; field-work-order routing efficiency improved; customer service queue handling improved through agent-assisted triage; market participation evidence overhead reduced (note: AI augments, does not replace, market-decision systems); regulatory reporting evidence aggregation accelerated. The metric is SAIDI/SAIFI improvement, work-order completion rate, and customer-NPS movement.
Common deployment patterns
Common deployment patterns for AU energy and utilities: agent-assisted outage management surfaced in the existing OMS workflow; predictive maintenance agents that surface in the work-order backlog rather than as a separate dashboard; customer service triage agents grounded in your billing and CIS data; field-mobility AI that operates offline-first given intermittent rural connectivity; SOCI Act-aligned deployment patterns; document-Q&A over network standards, operational procedures, and safety documentation.
Related Bedstone services
Energy and utilities operators typically pair this work with hybrid edge and cloud infrastructure, security audits for OT-IT boundary, operational and asset-monitoring agents, and sovereign AI deployment for SOCI Act-affected workloads. Or look at Bedstone OS for an internal AI workspace connecting SCADA, asset management, and field reports.
How we engage
Five-step delivery, scoped to fit. Audit, scope sprint, proof of concept, verification, rollout. Wrapped as a fixed-scope sprint, monthly retainer, fractional engagement, or one-off audit. See services for the full process and commercial structures.
Common questions about AI for energy
What does AI for energy typically deliver?
Three durable wins: asset failure prediction that reduces unplanned outages, demand forecasting that improves dispatch, and customer service automation that reduces inbound load. Each measurable against baseline.
Can you integrate with our SCADA, ADMS, or billing systems?
Yes. We integrate against OPC-UA for OT systems, against APIs for ADMS and billing, and work with utility-specific data formats.
Do you work with generators, networks, retailers, or all three?
All three. The workflows differ but the underlying engineering and regulatory context overlap significantly.
Is this eligible for R&D Tax Incentive?
Most novel agentic AI and integration work qualifies.
Across Australia
We work with energy and utilities operators across the country. See city-specific context: AI agency Australia, Brisbane, Sydney, Melbourne, Perth.