Building Atlas

Core Features

Building Atlas applies a data-driven methodology that links building characteristics, energy consumption, and regulatory context to emissions outcomes. It models carbon reduction potential at portfolio scale, enabling users to prioritise interventions based on emissions impact alongside cost and risk considerations. Some of its key capabilities are:

• Carbon Baseline Estimation: Generates initial estimates of building-level energy use and associated carbon emissions using AI and aggregated datasets.

• Emissions Reduction Modelling: Simulates how retrofit measures (e.g., insulation, electrification) affect carbon output over time.

• Portfolio Decarbonisation Planning: Aggregates emissions data across assets to support portfolio-wide carbon reduction strategies.

• Scenario Analysis for Carbon Pathways: Compares different retrofit scenarios based on emissions savings, timelines, and cost trade-offs.

• Carbon-Linked Risk Assessment: Identifies assets exposed to regulatory or market risks tied to poor emissions performance.

• Energy-to-Carbon Data Integration: Links building physics, energy consumption, and grid factors to estimate carbon impacts more consistently.

Closing Insights

Building Atlas was developed to address a structural gap in building decarbonisation: while buildings account for a large share of global emissions, retrofit planning has traditionally been slow, fragmented, and focused on individual assets rather than emissions at scale. The platform’s use of AI to rapidly generate carbon baselines and model reduction pathways reflects a shift toward treating emissions as a portfolio-level variable rather than a by-product of energy analysis.

Its users include commercial real estate owners and asset managers with differing carbon accounting priorities. Some focus on meeting regulatory thresholds such as minimum energy efficiency standards, while others use the platform to evaluate long-term decarbonisation pathways or to prioritise investments based on emissions reduction potential. In both cases, the platform links emissions data with financial and operational decision-making.

Recent positioning highlights its ability to connect emissions modelling with execution, including integration with financing and delivery partners. This extends its role beyond analysis into implementation, particularly in markets where carbon reduction targets, asset valuation, and capital planning are increasingly interconnected.