SenseCore was built around a frustration that most energy platforms were either too narrow or too reactive. Facilities managers and housing teams were drowning in data but still missing the insight that actually mattered — who is at risk, what will consumption look like tomorrow, and are we compliant?
The founding idea was to combine genuine AI forecasting with social responsibility tools like the Fuel Poverty Risk Score — something no competitor offers — all delivered through a single, clean API rather than yet another fragmented dashboard.
Olajide is the founder and sole engineer of SenseCore AI Ltd. His work bridges machine learning, building physics and UK energy regulation — the three disciplines SenseCore brings together in a single platform.
He has published five peer-reviewed papers on Zenodo covering the forecasting models, anomaly detection methods, occupancy inference and fuel-poverty scoring methodology behind SenseCore. The decision to train the platform's Temporal Fusion Transformer on the Building Data Genome 2 dataset — covering 1,112 commercial buildings across multiple climates — established the platform's sub-11% MAPE benchmark in half-hourly electricity forecasting.
He's based in London and builds SenseCore solo. Get in touch — or read the research.