Drones, Thermal Imaging, and AI: A faster way to fix leaky buildings and protect capital
Older assets bleed money through leaky roofs, aging windows, and weak insulation. Energy codes are tightening, budgets are finite, and guessing which retrofit pays back is expensive. Lamarr.AI, founded by a team out of MIT, turns that guesswork into a data-backed plan you can act on.
Order a scan, and the company coordinates drones, thermal and visible-range cameras, and AI to survey your building. The system flags issues, quantifies impact, and prioritizes upgrades with clear ROI. It also assesses structural conditions, builds a detailed 3D model, and maps every anomaly to exact locations on the envelope.
What sets it apart
- Root-cause diagnostics vs. generic "hot spot" maps: infiltration/exfiltration, missing insulation, water intrusion, and more
- Anomalies pinned to a 3D model of the building for precise scopes of work
- Automated cost and payback modeling using advanced energy simulations
- Portfolio-ready workflow: scan one building or a hundred with consistent outputs
Numbers that matter to owners and GCs
- Over $3M in avoided construction and retrofit costs to date through targeted interventions instead of full-system replacements
- Example scale: a 180,000-square-foot facility yields ~2,000 images; models analyze them in seconds, not weeks
- Envelope failures drive significant defects; airtightness and insulation are low-hanging opportunities for energy savings and durability
For context on energy codes and envelope performance, see the U.S. Department of Energy's Building Energy Codes Program here.
Field results
In partnership with the City of Detroit, Lamarr.AI inspected three municipal buildings. Across two of them, the system identified more than 460 issues including insulation gaps and water leaks. Modeled upgrades like targeted weatherization and window replacements showed up to 22 percent HVAC energy reduction. The full process took days, and the drone flight used an off-site operator, pushing scalability even further.
How it works (simple flow)
- Book a scan online and choose timing
- Lamarr.AI dispatches trained partners with off-the-shelf drones and a flight plan
- Thermal and visible images are captured and uploaded
- AI runs computer vision on anomalies and builds a 3D model
- You receive a report with root causes, cost ranges, and ROI for each fix
What you get in the report
- 3D anomaly map with precise locations across roofs, walls, windows, and interfaces
- Classification of issues: air leakage, insulation voids, moisture and water intrusion
- Prioritized retrofit list with estimated costs and modeled payback
- Exportable insights for scopes, bids, and capital planning
Built for portfolio operators
Facilities teams don't have time for one-off, manual audits on every asset. Lamarr.AI scales the same process to campuses and multi-site portfolios. Consistent reports, comparable KPIs, and a shared data model help shift from reactive work orders to strategic asset management.
Where this fits in your workflow
- Pre-acquisition due diligence: quantify envelope risk and near-term capex
- Budget planning: stack-ranked retrofits with ROI to defend capital requests
- Design and construction: verify installation quality and catch envelope defects early
- Operations: schedule targeted weatherization and track improvement year over year
- Compliance: prepare for energy performance standards with documented savings
From research to jobsite
Lamarr.AI was founded in 2021 by CEO Tarek Rakha PhD '15, Professor John Fernández, and Research Scientist Norhan Bayomi SM '17, PhD '21. The core tech grew from MIT research, Syracuse University development, and a $1.8M U.S. Department of Energy award. The company's name honors Hedy Lamarr, whose invention laid groundwork for secure communications.
Bottom line for owners, FMs, and AEC teams
- Find the real cause of energy loss and moisture issues, fast
- Spend on fixes that pay back and extend asset life
- Standardize diagnostics across sites with a repeatable process
- Reduce audit costs and push work to the right contractors with clear scopes
If your team is also building practical AI skills for operations and capital planning, explore focused training by job role here.
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