Sera deployed as the intelligence layer above the existing climate computer and energy data, ingesting boiler logs, pipe temperatures, climate commands, weather, and the grower’s heating protocols/SOPs. It continuously reasoned over thermal dynamics, hardware response, and crop needs to:

• Predict and explain heat-up/cool-down accurately: "Boiler needs 28 min to reach +2 °C pipe delta from current load—current ramp schedule undershoots by 12 min."

• Recommend protocol-aligned optimizations: Adjust min runtime, load-shed thresholds, circulation timing, or vent minimums to eliminate short-cycling and align with demand windows.

• Deliver root-cause insights via assistant: Ask "Why pipe temp lagging during sunrise?" → "Lag from boiler short-cycling (cycle avg 4.8 min vs. target 10 min) + circulation delay; minor RH +4% impact. Suggestion: Raise min runtime 2 min per your winter protocol."

• Automate smart control loops: Shift from fixed schedules to demand-aware orchestration—activate/shut down boilers precisely, suppress unnecessary runs, and route high-priority alerts only when crop-relevant.

• Enforce consistency: Knowledge Base captured their best heating rules and site quirks so every recommendation stayed tailored, repeatable, and safe—no generic overrides.

No new sensors or major hardware changes—just smarter interpretation of existing data to close efficiency gaps.