Climate Ltd builds the Climate Action Platform: sixteen AI agents on one data spine that collect data automatically, build the emissions inventory, model risk and decarbonisation with real climate science, and keep disclosure accurate — for a single organisation or a whole portfolio.
Emissions accounting, risk analytics, decarbonisation planning and disclosure grew up as separate jobs, done by different tools, different consultants, often different teams in the same organisation. The result: a fragmented stack, rebuilt by hand every cycle, on top of a regulatory map that keeps changing.
We built one platform instead. Agents fetch the data. The same data builds the inventory, feeds the risk models, prices the decarbonisation pathway, and drafts the disclosure — so every number agrees with every other number, and nothing gets rebuilt from scratch.
Each of the sixteen agents owns one job end to end: its own data sources, its own scientific or calculation standard, and a write-back into a ledger the other agents can query. That’s deliberate — it’s what lets an inventory figure, a risk exposure and a disclosure line all agree with each other, because they come from the same underlying records.
We publish our research openly. Our research group maintains a series of working papers benchmarking AI-enabled climate platforms against what a genuinely unified platform needs to do — derived from real regulatory and methodological requirements, not feature-list marketing. Climate Ltd’s own architecture is assessed in that same framework, and treated, like every platform reviewed, as self-reported and not independently audited.
Climate Ltd is led by people who have spent decades at the intersection of climate science, finance and technology: running large organisations, advising cities on climate resilience and adaptation planning, and leading engineering and data teams at global scale. That experience shapes how the platform is built — rigorous, transparent, and built for people who will be personally accountable for the numbers.
Leadership experience running and advising large organisations through operational and regulatory complexity, not just studying it from the outside.
Direct experience advising cities and public bodies on climate resilience and adaptation planning at scale.
Backgrounds leading engineering and data teams building systems people rely on — the discipline that shapes how the agent architecture is governed.
The platform doesn’t invent its own methodology. It implements the ones your risk team, auditor and investors already recognise.
Standard global climate models are too coarse for a single asset or facility. We use downscaled climate models — informed by established global and regional climate science — for a more accurate, localised read on physical hazard than a global average gives you.
Transition scenarios aligned to recognised frameworks; downscaled physical hazard modelling for heat, flood, drought, wildfire and cyclone; entity-level aggregation for portfolio and whole-book stress testing; PCAF-aligned financed-emissions methodology.
GHG Protocol Corporate Standard and Scope 3 Standard; ISO 14040/14044 for life cycle assessment; marginal abatement cost curves and adaptation ROI pricing, treated as one input to a broader decision process — not a static, self-sufficient ranking.
We take the documented limits of these methods seriously — downscaling can inherit bias from its source model, MACC curves can miss interaction effects between levers, and multi-agent AI systems can fail in ways a single model doesn’t. That’s why every agent output stays reviewable and traceable to source, rather than presented as a black-box answer.
An agent that gets a number wrong quietly is worse than no agent at all. Every calculation and model run is reviewable, every mapping and assumption is confirmed rather than silently re-guessed, and every reported figure traces back to its source.
Agents propose; your team confirms. Calculation rules, scenario assumptions and emission-factor mappings are visible and editable, not hidden inside a model.
Exportable audit trails showing source data, formulas and every calculation step, with an optional pre-assurance review before a filing reaches your external auditor.
Regulatory scope shifts constantly across this industry. The platform is configured per jurisdiction, not rebuilt.
Founded in Australia, with people now working across North America, the UK, Europe, the Middle East and India — close to the regulatory and market detail in each place we serve.
We’re building the team across climate science, risk and decarbonisation modelling, regulatory research and applied AI. If manually re-keying an emissions inventory has ever made you angry, we’d like to talk.
Email careers@climate.ltd
