Grid-edge inference, demand response, BESS coordination, and EV charging optimisation at scale
Auralink delivers the strongest energy-sector proof in our portfolio: distributed EV charging network AI with 78% autonomous incident resolution in simulated operations, 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.
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 simulated EV-charging operations is the reference proof of the architecture.
Based on common industry needs
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
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
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
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
The Full-Stack Physical AI layers most relevant to this sector.
A 30-minute call is enough to diagnose whether your AI initiative is stuck for industry-specific reasons — and what to do about it.