PassiveLogic, which creates digital twins of buildings, lands $34M

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Commercial building systems often require engineering teams with years of training to maintain. Even retrofitting old buildings with technology like HVAC systems can be costly and time-consuming — not to mention error-prone. The construction labor shortage only threatens to execrate the challenges, with the U.S. Chamber of Commerce reporting that 70% of contractors are struggling to meet project deadlines.

As digital simulation gains currency in other domains, some vendors are pitching “digital twin” technology as a partial solution to ongoing construction hurdles. Digital twins are virtual representations of systems that span their lifecycles and use machine learning to help with decision-making. Platforms like London-based SenSat assist clients in construction, mining, energy, and other industries with creating models of locations for projects that they’re overseeing. Meanwhile, companies including GE offer products that allow companies to model digital twins of actual machines and closely track performance.

Another vendor in the growing digital twin technology market is PassiveLogic, which today announced that it raised $34 million in series B financing — bringing its total raised to $53.2 million. Founded in 2016, PassiveLogic uses AI-powered “deep physics” models to enable customers to design, build, operate, and manage both buildings and building controls.

Digital twins for buildings

Troy Harvey and Jeremy Fillingim, entrepreneurs with backgrounds in hardware engineering, teamed up to found PassiveLogic with the goal of bringing autonomous controls to the building construction sector — which is worth more than $1 trillion. The Salt Lake City, Utah-based company’s software environment allows users to build models by drawing schematics and then generates a physics-based digital twin that can be deployed via PassiveLogic’s control hardware.

PassiveLogic creates virtual analogs that try to mimic the behavior and interactions of their real-world counterparts. Algorithms attempt to understand how a building’s equipment and systems interact, allowing local, in-building AI to make control and management decisions for maintenance and operations.

Image Credit: PassiveLogic

A key consideration in deploying digital twin technology is data accuracy, of course — the models are only as good as the data that’s used to develop and maintain them. Companies facing data quality, reliability, management, and governance issues aren’t likely to find success with digital twin platforms unless they heavily audit and correct for those issues.

As Gartner notes in a report: “It is difficult to anticipate the nature of the simulation models, data types, and data analysis of sensor data that might be necessary to support the design, introduction, and service life of the digital twins’ physical counterparts. While 3D geometry is sufficient to communicate the digital twin visually and how parts fit together, the geometric model may not be able to perform simulations of the behavior of the physical counterpart in use or operation. At the same time, the geometric model may not be able to analyze data if it is not enriched with additional information. [Moreover,] digital twins with long life cycles … [might] extend well beyond the lifespans of the formats for proprietary design software that most likely were used to create them and the means of storing data.”

PassiveLogic aims to head off some data challenges with hardware controllers and sensors that enable connectivity to building systems, providing an edge platform for sensors, equipment, and the internet of things (IoT). The devices are designed to support new and older buildings and campuses including hospitals and datacenters throughout jobs like programming, installation, and commissioning.

Exploding competition

Utility-optimizing AI is a burgeoning business with plenty of demand. Gartner predicts that at least 50% of manufacturers with annual revenues in excess of $5 billion have at least one digital twin initiative launched for either products or assets. Analysts at the firm predict, moreover, that the number of organizations using digital twins will triple by the end of 2022.

In addition to PassiveLogic, there’s BrainBox, Aquicore, and Mesa, whose algorithms make fine-grained adjustments to HVAC systems on the fly. Augury, a startup developing sensors that attach to machines and record data that are then analyzed in the cloud, works with service companies to diagnose and optimize systems like industrial HVAC. And Carbon Relay leverages sensor data to make predictions about datacenters’ cooling usage.


PassiveLogic — which has roughly 70 employees — claims its customer base includes building owners, operators, architects, engineers, contractors, and utility partners. The company is still in the pre-product phase, with plans to launch a beta and general release later this year.

“PassiveLogic’s generalized autonomy platform is ideally suited to buildings, which are complex control systems requiring entirely customized solutions … However, the technology will have an equal impact on other complex systems like energy grids, logistics and supply chain facilities, networks, and other critical infrastructure,” Harvey told VentureBeat via email. “The pandemic has actually spurred interest in safer and more comfortable working spaces, and buildings that are responsive to human needs. As employers and building owners contemplate usage in a post-pandemic world, we believe that autonomous, energy-efficient buildings will be a critical asset.”

Addition, Keyframe, RET Ventures, Brookfield, and Era Ventures participated in PassiveLogic’s latest funding round.

Originally appeared on: TheSpuzz