Deepki, a leading sustainability SaaS provider for the real estate sector, has unveiled a new generation of expert-supervised AI Agents aimed at turning complex sustainability data into practical, performance-driven insights. The launch marks a major step in helping real estate owners, investors, and operators improve asset performance while strengthening profitability and regulatory compliance.
At the core of this innovation is Deepki’s AI Lab, where in-house specialists collaborate closely with clients to train, test, and validate AI Agents using real estate, financial, and sustainability datasets. This human-in-the-loop approach is designed to ensure that AI outputs are accurate, relevant, and directly applicable to real-world decision-making, rather than relying on generic or unverified models.
Built on More Than a Decade of Data Expertise
Deepki’s AI capabilities are the result of over 11 years of continuous data collection and innovation in sustainability analytics. Machine learning has been embedded into the platform since its inception, gradually evolving to include deep learning and, more recently, generative AI technologies. These include both Large Language Models and more adaptable Small Language Models tailored to specific use cases.
Over time, this evolution has enabled a wide range of advanced features, such as automated data extraction from documents like energy performance certificates, audit reports, and technical assessments. The platform also enhances data quality, automates reporting processes, and delivers deeper insights through tools such as fault detection, virtual retrofit simulations, and hybrid SaaS interactions. This long-standing AI foundation now allows Deepki to deploy domain-trained AI Agents at scale with a high degree of reliability.
Accurate, Decision-Ready AI for Real Estate
Deepki’s approach to AI is rooted in the belief that the real estate industry cannot afford opaque or approximate solutions. Reliable decisions depend on precise, verified property data and models that reflect the complexity of real assets. By training its AI Agents on high-quality, audit-ready data, Deepki positions itself as a platform capable of delivering actionable insights for retrofit planning, sustainability strategies, and financial impact assessments.
The AI Agents are developed collaboratively by Deepki’s internal experts and its clients, ensuring they account for the nuances of different asset classes. They draw on a proprietary database covering more than 500,000 assets across over 80 countries, giving the models a depth and diversity that enhances accuracy. This combination of scale, data quality, and sector expertise differentiates Deepki’s AI from more generic solutions trained on open or unverified data.
Trust, Security, and Responsible AI
Trust is a central pillar of Deepki’s AI strategy. All models are trained on fully anonymized datasets and processed within secure environments that comply with ISO 27001 and SOC 2 Type II standards. This responsible AI framework ensures data protection while maintaining transparency and reliability in model outputs.
Early Results Show Strong Performance Gains
Several clients are already piloting Deepki’s virtual sustainability agents across asset classes such as retail, offices, and light industrial properties. These early adopters in Europe and the U.S. are working closely with the AI Lab to fine-tune the agents and maximize operational value.
Initial feedback points to substantial efficiency improvements, with scenario modeling and financial analysis times reduced by 20% to 80%. The results are also proving more accurate than those generated by generic AI tools, making the solution particularly valuable for large-scale, multi-geography retrofit programs operating under diverse regulatory requirements.
With this launch, Deepki reinforces its position at the intersection of AI, sustainability, and real estate performance, offering a scalable and trustworthy path toward smarter, greener portfolios.
