Starting in energy. Expanding by design.

Energy is where RunnerTau is proven. RunnerTau 7B and 4B already reason about energy problems the way a domain expert would — understanding battery systems well enough to explain charge behavior, flag abnormal degradation, and reason about dispatch decisions against real operating constraints.

This is also where our consultancy engagements start: assessing whether an energy operator's telemetry, documentation, and asset context are reasoning-ready, then building the TEMPOral knowledge layer that lets RunnerTau reason over their specific assets.

Data centres share the same underlying physics as energy assets: power draw, thermal limits, and capacity constraints that telemetry alone doesn't explain. As compute density rises, the questions operators need answered — can we admit this workload, is this rack's telemetry trustworthy, will cooling hold — are time-series reasoning problems.

We're extending RunnerTau's energy-domain reasoning into this vertical next, building on the same asset-grounding approach already proven with battery systems.

Automotive powertrains and battery packs are, structurally, the same reasoning problem as stationary battery systems — charge and discharge behavior, degradation, and thermal limits — with the added complexity of mobility and fleet-level telemetry.

Having proven RunnerTau's reasoning on stationary battery systems in energy, automotive is a natural extension of the same underlying model family.