Applied AI for Energy Operations
Orbital is an applied AI system designed to work alongside operators and engineers in complex energy environments. It brings together high-fidelity data, physics-based understanding, and explainable AI to support better day-to-day operational decisions.
At India Energy Week 2026, we are sharing a positive and practical vision for how AI can augment frontline teams, improving reliability, efficiency, and confidence across refining, power, and large-scale energy infrastructure.
Why AI Hasn’t Transformed Core Operations
AI adoption in energy has largely stalled at the edges. Despite decades of investment, most deployments remain confined to:
Postfacto analysis on historian data
Predictive maintenance dashboards
Inspection and backoffice optimisation
The core of operations, the control room; remains largely untouched.
Why?
Critical data lives in DCS and Level2 systems, not fully historised
Blackbox models cannot be trusted during abnormal operations
Engineers are still required to justify decisions using physics
Cloudfirst AI architectures do not align with OT realities
This scepticism is justified.
A Different Approach:
Orbital was built from first principles for heavyindustry operations.
It is not a generic AI platform adapted for energy. It is an operatorgrade system that unifies:
Highfidelity timeseries learning from process data
Physics based reasoning calibrated continuously against reality
Contextual AI that understands equipment, flows, and constraints
Deployed flexibly across cloud, onpremises, or hybrid architectures, aligned to each organisation’s security, scalability, and operational requirements.
How Orbital Works
Orbital operates as a coordinated multiagent system:
Observe
Ingests timeseries data from DCS, historians, and LIMS
Learns normal behaviour, drift, and operating envelopes
Forecasts key variables under real operating conditions
The system continuously critiques itself, reducing false positives and improving robustness over time.
What Orbital Enables
Prediction
Anticipate the future behaviour of complex processes under real operating conditions. Orbital forecasts key variables, constraints, and degradation patterns early enough for teams to plan, intervene, and operate with confidence.
Optimisation
Continuously compare current operating conditions against physics-informed optimal states. Orbital identifies feasible pathways to improve throughput, energy efficiency, product quality, or emissions and clearly explains the trade-offs involved.
Real-Time Soft Sensing
Infer lab-grade or hard-to-measure properties in real time, reducing delays and dependence on offline testing, even during sensor faults.
Explainable Diagnostics
Detect emerging issues early and explain root causes using physics and process context, not opaque scores.
Early Degradation Detection
Identify subtle shifts in equipment or material behaviour that traditionally require inspection or long-term trending.
Shared Operational Intelligence
Act as a common AI reference point for operators, engineers, reliability teams, and digital leaders, capturing institutional knowledge as it evolves.
Designed for Operational Reality
Orbital is architected to align with how modern energy organisations are evolving their IT and OT landscapes.
The platform supports cloud-native, onpremises, and hybrid deployments, allowing teams to choose the model that best fits their security posture, data strategy, and scale ambitions.
Cloud deployment for rapid scaling, centralised learning, and multi-site rollouts
Orbital integrates cleanly with existing control systems and data platforms, operating in an advisory, humanintheloop mode. It enhances decision-making without disrupting established control or safety layers.
Operational Clarity for Your Teams
Control Room Operators
Early warnings, clear explanations, fewer surprises.
Process Engineers
Physicsaligned insights, faster rootcause analysis, better optimisation decisions.
Reliability & Integrity Teams
Early indicators of degradation and emerging risk.
Digital & OT Leadership
A deployable, auditable AI architecture aligned with security and governance requirements.
Why Now
Orbital represents a shift from analytics after the event to intelligence during operations, grounded in physics, validated by data, and trusted by engineers.
Energy systems are becoming more constrained, more complex, and more scrutinised. Incremental digital tools are no longer enough.
Meet Us at India Energy Week 2026
We are hosting closeddoor conversations during IEW to discuss:
Frontline AI for refining, power, and largescale energy systems
Pilot discovery and technical deep dives
Indiaspecific deployment and scaleout strategies
Request a Conversation