Buildings are responsible for 40% of the United States’ emissions (and 18% in Canada), largely due to fossil fuel-based heating systems and electricity use. At the current rate of building energy assessments and upgrades, it will take over 140 years to retrofit all of North America’s buildings to net zero by 2050. This problem can’t be solved the old-fashioned way.
As a data scientist working in the climate tech space, I’ve had a front-row seat to witnessing how a commitment to responsible AI isn’t just rhetoric. It delivers measurable, mission-aligned impact for our business and the planet.
Climative uses AI to rapidly generate millions of personalized energy transition and climate adaptation plans for homes. Homeowners get actionable advice to improve their home’s comfort, affordability, emissions, and resilience. Our customer engagement tool provides powerful data for banks, insurance companies, utilities, and governments to make informed decisions, such as financing retrofits, targeting incentives, and managing climate risk.
Our platform utilizes a combination of geospatial analysis and predictive modeling to assess energy use, emissions, and retrofit pathways across entire communities—automatically and in real time. In this article, I’ll share how our AI principles drive customer engagement, climate impact, and company growth.
A Quick Word on the Automated Carbon Model (ACMTM)
Climative’s core IP is the Automated Carbon Model (ACM), a suite of machine learning algorithms that quickly and cost-effectively evaluate the energy efficiency and carbon footprint of homes. The ACM was trained on an extensive dataset containing building structure information and modeled energy results for over 600,000 pre- and post-retrofit on-site home energy audits.
Millions of these building-level home energy assessments can be completed per day, providing personalized retrofit advice to homeowners and enabling macro-level decision-making power to various stakeholders. The ACM greatly accelerates the status quo: on-site energy assessments that take hours to complete and 200+ inputs. The ACM achieves 80% accuracy with fewer than 10 inputs from public data sources, such as property assessments, energy costs, and weather data.
Designing Models for Trust, Accuracy, and Equity
Our Responsible AI Framework isn’t a checkbox exercise—it’s a living guide embedded in every stage of data ingestion, model development, and deployment. The framework prioritizes:
- Transparency & Interpretability: We provide clear reasoning for each retrofit suggestion.
- Privacy-by-Design: Personal homeowner data is anonymized and tightly controlled.
- Fairness & Bias Mitigation: We test models across diverse home types and geographies, ensuring less privileged households receive equitable treatment.
By operationalizing these principles, we not only reduce risks but build trust with homeowners, financial institutions, utilities, and regulators alike—a foundation for scalable impact.
Creating Scalable Products with Responsible AI
At the core of Climative’s platform is a scalable, privacy-first data architecture that supports three integrated products—Climative Insights, Advisor, and Navigator—each built to deliver accurate, actionable outcomes for different stakeholders.
- Climative Insights powers bulk energy modeling and carbon profiling across entire building portfolios or municipalities. This API-based platform generates consistent and comparable estimates across millions of homes, using AI trained on a diverse blend of geographic, building, and energy datasets.
- Climative Advisor equips energy professionals with remote assessment tools that are faster, more consistent, and about 80% accurate compared to modeling software used for in-person audits.
- Climative Navigator engages homeowners directly, offering tailored retrofit suggestions, financial guidance, and a clear path from interest to action.
All three are underpinned by the same responsible AI principles—bias testing, explainability, and privacy protection—and continually improve based on real-world performance data. This unified foundation enables rapid scaling while preserving trust, accuracy, and relevance across every deployment.
Using Responsible AI to Drive Real Impact
Our responsible AI principles are paying off. Our customers are using Climative to accelerate homeowners’ retrofit journeys, making their homes more comfortable, affordable, and with lower emissions. Over the past few years:
- Climative has generated energy transition plans for over 6 million homes, utilizing AI to quickly and cost-effectively evaluate a building’s efficiency and carbon footprint and present a personalized retrofit pathway.
- These assessments have identified potential CO₂e reductions of 55 megatons in 682 municipalities—roughly equivalent to removing 12 million cars from the road for a year.
- 9X higher enrolment for virtual home energy assessments compared to traditional on-site home assessments
- 4X high click-through rates for home energy assessments when homes are pre-assessed using AI
Transparent AI Practices and Trust Win Business
Climative is in an emerging yet competitive segment. We’ve noticed that our commitment to transparent and equitable use of AI gets us in the door with customers, and our product stands up to hard scrutiny to win big business.
Revenue has grown exponentially over the past 3 years, driven by contracts that cover 50% market share in Canada and early adopters in key U.S. states. This rapid yet sustainable growth demonstrates a high demand for trustworthy, scalable retrofit insights to drive customer engagement and mitigate climate impact. Our credibility and reputation as responsible stewards of sensitive data are driving this momentum, which in turn is shortening the sales cycle as we expand.
Data-Driven Governance & Continuous Improvement
At Climative, we are committed to our Responsible AI Framework and rigorously evaluate the performance of our energy assessment and retrofit recommendation models. To ensure the reliability of our models, we systematically compare our estimates with untouched historical on-site energy assessment data, measuring both accuracy and consistency.
To further validate our approach, we have participated in double-blind tests conducted by various independent third parties. These evaluations consistently demonstrate that our remote assessments yield reliable results comparable to those of traditional on-site methods.
Our Responsible AI Framework is aligned with emerging ethical standards in Canada, the U.S., and the EU, enabling us to meet and exceed compliance expectations while fostering trust with our partners. Through our ongoing commitment to transparency and rigorous testing, we ensure our AI systems remain fair, accurate, and adaptive.
What’s Next: Scaling with Responsibility
Looking ahead, we’re expanding the reach of our Responsible AI principles into new domains. We are advancing AI models that account for geographic variation, building typologies, and localized emissions data to improve precision at scale. Our platform is evolving to support program-level impact tracking—quantifying carbon reductions across entire retrofit cohorts, not just individual homes.
We’re also investing in interoperability, ensuring compliance with emerging standards like PCAF’s standard on financed emissions, ASHRAE standards, and the EU’s forthcoming AI Act. We embed financial inclusion directly into our models, enabling features like carbon credit readiness and green mortgage scoring—tools that connect climate action with access to capital.
Each of these developments moves us further along the path from principle to measurable outcome—delivering not just responsible AI but scalable climate solutions.
At Climative, responsible AI is our superpower for saving the planet. By embedding ethics, transparency, testing, and continuous governance into everything we build, we hope to improve trust in AI as a tool for good.
