Grid-edge inference, demand response, BESS coordination, and EV charging optimisation at scale

AI for Energy & Infrastructure

Auralink delivers the strongest energy-sector proof in our portfolio: distributed EV charging network AI with 78% autonomous incident resolution, real-time BESS and solar coordination, OpenADR demand-response integration, and grid-balancing across distributed charging assets (arXiv preprint 2603.08736). ABB E-mobility A400 (400 kW ultra-fast charging) rounds out the infrastructure depth. We bring IEC 61850, IEC 62443, NIS2, and OpenADR discipline to grid-edge AI — not as a compliance add-on but as the architecture constraint from day one.

78%

Autonomous incident resolution (Auralink EV charging)

IEC 62443

OT cybersecurity standard

IEC 61850

Substation communication standard

What Keeps Energy AI Teams Stuck

Grid-edge inference: solar and wind intermittency requires sub-second dispatch decisions that SCADA-only architectures cannot make — but placing AI inside the OT perimeter triggers IEC 62443 Zone 3/4 controls

BESS and demand-response coordination: battery state-of-charge optimisation, OpenADR signal parsing, and grid-frequency response must run on sovereign, on-prem infrastructure — cloud latency is incompatible with real-time balancing requirements

Fault detection and self-healing: anomaly detection models generate excessive false positives on noisy SCADA telemetry — operators disable alerts, leaving the AI investment idle

EV charging fleet optimisation: orchestrating hundreds of distributed chargers across varying grid tariff zones, local generation assets, and demand-response obligations requires multi-agent coordination rather than a centralised scheduler

Substation edge inference under NIS2: energy operators classified as essential services face mandatory OT security under NIS2 Directive — deploying AI inference on substation hardware without a validated IEC 62443 security plan creates regulatory exposure

How We Help

We design energy AI architectures for operational technology constraints — real-time inference inside the IEC 62443 OT perimeter, sovereign on-prem deployment with no cloud dependency, and IEC 61850 substation protocol integration. Our Advise/Build/Train model covers grid-edge AI architecture (Advise), full-stack build of BESS coordination and EV charging orchestration systems (Build), and capability transfer to DSO or utility engineering teams (Train). Auralink's 78% autonomous incident resolution in EV charging is the live proof of the architecture.

Recommended Services

Based on common industry needs

AI Strategy Sprint

Four weeks to a strategy document, a business case, an ROI model, and a 12-month execution plan — scoped for industrial operators where OEE, safety-regime timelines, and physical-system procurement cycles are the real constraints, not just board optics

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Agentic System Engineering

Twelve weeks to a production-grade multi-agent system that serves as the software and control-plane complement to your cyber-physical stack — fleet intelligence, SCADA-adjacent orchestration, or autonomous operations — with the eval harness, the observability stack, and the SRE handoff your team needs to operate it

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Pilot-to-Production Hardening

Twelve weeks to harden an edge or embedded AI pilot stuck before production — on constrained hardware, inside safety envelopes, under latency and reliability requirements the pilot was never designed to meet

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EU AI Act Compliance Program

Twelve to twenty-four weeks to risk-classify your AI systems, complete the conformity assessment, produce the Annex IV technical documentation, and stand up post-market monitoring — with special depth on Annex III high-risk categories for autonomous, industrial, and robotics deployments

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Track Record

Auralink EV charging AI: 78% autonomous incident resolution — real-time BESS and solar coordination, OpenADR demand-response, grid balancing across distributed infrastructure (arXiv preprint 2603.08736)ABB E-mobility A400: 400 kW ultra-fast charger integration — charging infrastructure engineering at grid scaleIEC 62443 OT security and NIS2 compliance architecture — production AI inside the operational technology perimeter

Capabilities for this industry

The Full-Stack Physical AI layers most relevant to this sector.

Embedded & Edge Systems

Real-time control and AI at the edge — from silicon and RTOS to on-device inference.

Industrial RAG & Knowledge

Answers grounded in your manuals, specs and standards — traceable to source.

Physical-AI Safety & Security

The independent boundary that constrains, monitors and fails safe.

Your Industry Has Specific Physical AI Challenges. Let's Address Them.

A 30-minute call is enough to diagnose whether your AI initiative is stuck for industry-specific reasons — and what to do about it.

All Industries

Grid-edge inference, demand response, BESS coordination, and EV charging optimisation at scale

AI for Energy & Infrastructure

78%

Autonomous incident resolution (Auralink EV charging)

IEC 62443

OT cybersecurity standard

IEC 61850

Substation communication standard

What Keeps Energy AI Teams Stuck

Fault detection and self-healing: anomaly detection models generate excessive false positives on noisy SCADA telemetry — operators disable alerts, leaving the AI investment idle

How We Help

Recommended Services

Based on common industry needs

Track Record

Capabilities for this industry

The Full-Stack Physical AI layers most relevant to this sector.

Embedded & Edge Systems

Real-time control and AI at the edge — from silicon and RTOS to on-device inference.

Industrial RAG & Knowledge

Answers grounded in your manuals, specs and standards — traceable to source.

Physical-AI Safety & Security

The independent boundary that constrains, monitors and fails safe.

Your Industry Has Specific Physical AI Challenges. Let's Address Them.

A 30-minute call is enough to diagnose whether your AI initiative is stuck for industry-specific reasons — and what to do about it.