Faster rigorous answers, on real networks.
DNSPs and TNSPs use AgenticGrid to model demand-management scenarios at address-level granularity, run AER-aligned cost-benefit analysis in minutes, and produce RIT-D and hosting-capacity outputs a regulator can audit. The platform is live with four Australian networks today.
Distribution networks
From demonstration to live pilots.
Essential Energy moved from a January 2026 demonstration to a scoped proof-of-concept and then to live microgrid-sizing pilots for two remote NSW communities — the platform is informing real supply decisions as we write.
Energy Queensland demonstrated to the planning team and indicated strong interest in a regional Queensland pilot. Ausgrid engaged deeply on per-substation load allocation and DSO strategy.
Transmission
A bottom-up picture of what shows up at your interface.
For a TNSP — and it's no accident that Transgrid is the program's industry funder — the value is a bottom-up, behaviourally-grounded picture of how distributed energy resources will reshape the loads you see at the zone-substation boundary. Every scenario produces a transmission-level rollup: peak import, peak export, load factor, and the reverse-power-flow extremes that drive transmission capacity requirements.
High-solar futures often invert what the network was built for — peak export exceeding peak import by multiples, on networks already close to their hosting envelope. The single hardest thing for transmission planning to anticipate, now visible per transformer.
What the platform surfaces
The shape of the analysis, not a sales pitch.
Every scenario AgenticGrid runs produces the same family of outputs. The numbers are yours — these are the categories:
Hosting-capacity utilisation per transformer + per feeder, voltage and thermal limits flagged. Trigger thresholds for augmentation or active management, surfaced before they bite.
Behind-the-meter, community-scale and hybrid storage sized and sited under AER CBA Guidelines v3. The platform tells you which configuration passes the test and which doesn’t — and why.
Today’s solar export becomes tomorrow’s EV import. The same scenario library models both horizons so investment is chosen with both in view.
Resilience storage assessed honestly. Full-coverage outage backup rarely passes CBA alone; the platform surfaces stacked-benefit configurations that do.
Every distribution scenario rolls up to the zone-substation boundary: peak import, peak export, reverse-flow extremes, load factor. TNSP-grade rollups from a DNSP-grade twin.
Every scenario ships with a Model Confidence Report — Pearson R against measured load, data-quality and temporal-coverage scores. We report the ceiling honestly so you know how much each finding can bear.
Every figure is reproducible from the underlying data and code. The platform reports its own confidence with each result.