AmpsPump

Summary

AmpsPump is a software-defined distributed energy platform — the intelligent layer that sits between the electric grid and energy demand. The charging endpoint is one application running on top of an energy server that also stores, routes, arbitrates, and protects power; the platform's defining property is that each deployed unit starts single-purpose and gains capability over time purely through software and storage expansion, without hardware replacement. An entry-level charging node and a continental-network node run the same base operating system; what changes is which intelligence and energy services are activated. The architecture follows a deliberate hybrid split: central intelligence for coordination, edge intelligence for execution. A fleet-level coordination layer optimizes across the whole network; a node operating system governs every site; a secure inter-site communication layer connects them; a site energy-orchestration layer manages local power flows; and an embedded AI inside each energy server makes real-time decisions locally — so a site keeps charging vehicles, managing its battery, and enforcing safety limits even when cloud connectivity is degraded or unavailable. The embedded AI is not a single model but a suite of purpose-built engines sharing one local execution environment: a forecasting engine (demand, renewables, weather, battery degradation, grid congestion), an operational-protection engine (anomaly and threat detection), a fleet-optimization engine (charging schedules and vehicle readiness), and a utility-facing engine (demand response and capacity participation). Two properties are suite-wide: local autonomy — keeping a node operating through degraded communications or grid events — and continuous learning, where site-level intelligence feeds back to improve the network's forecasts, operational policies, and the design of future units. Structurally, the system is multi-agent: a population of autonomous local decision-makers (one embedded AI per energy server) that act independently by default, coordinate through the communication and orchestration layers, and defer to higher-level coordination when a broader objective requires it — switching the network's posture between economic-efficiency optimization in normal conditions and resilience mode under grid stress.

Ecosystem surfaces addressed

What we built

Details forthcoming.

Outcome

Details forthcoming.