Agentic AI in energy is moving toward hybrid systems, not edge-only or cloud-only autonomy. In Europe, roles split across cloud optimization, edge control, and infrastructure layers. Preflet is an edge-first approach. The future is physical AI combining edge execution with cloud coordination.
Traditional BMS and EMS platforms fall short of enabling autonomous buildings, while cloud SaaS lacks the deterministic latency and safety needed for closed-loop control. Learn why an edge-first, hybrid model ensures operational excellence and where cloud-only options fail.
Preflet among winners of the ESA BA Challenge at the INNOspace Masters, securing a €100,000 grant. The platform leverages satellite data to optimize building energy management and reduce carbon emissions.
Experts at Hochschule Reutlingen explored what truly improves energy systems. Preflet added insights from its work on Edge AI Autonomy, which goes beyond continuous monitoring to enable dynamic control with a clear record of every action and its impact.
What happens when buildings get a digital colleague? Instead of showing slides or dashboards, we filmed a simple mini-series: 7 Days with LEO. In just one week, LEO supported a Head of Operations across 30+ sites — detecting anomalies, orchestrating resources, and preparing board-ready insights. Watch the Episodes Why It Matters
The next leap in energy management is orchestration powered by AI, not more dashboards. Join us at #FTF25 to see how LEO helps multi‑site companies reduce energy waste and improve performance.
In this interview, Francesca Rubbiani explains how their AI digital assistant, LEO, simplifies fragmented building data to cut energy costs and lower emissions. She also shares her startup journey and discusses the company’s strategic expansion into Germany.
From Madrid to Paris, Preflet used South Summit and VivaTech to demonstrate LEO, deepen corporate engagement, and accelerate its path toward energy intelligence
The 11th InnoPartner Kraichgau meeting focused on energy and regulatory challenges, where Preflet demonstrated how LEO brings structure and clarity to scattered operational data.
The KYP Score by Preflet evaluates a building's energy efficiency using benchmark data and statistical models. It helps identify areas for improvement, enabling energy savings, emission reductions, and financial benefits. Get insights to optimize performance and sustainability!
AI agents in building energy management must bridge the gap between capability and reliability. With strategies like zero-shot forecasting, MCP Protocol, and IoT-LLM model, these agents can optimize energy use while ensuring consistent performance.
Verifying energy savings boosts efficiency, reduces risk, and strengthens investor confidence. IPMVP and ICP cut due diligence costs, while rising energy prices accelerate payback periods.