architecture
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As the fight against climate change heats up, Cove.Tool is looking to help tackle carbon emissions one building at a time.
The Atlanta-based startup provides an automated big-data platform that helps architects, engineers and contractors identify the most cost-effective ways to make buildings compliant with energy efficiency requirements. After raising an initial round earlier this year, the company completed the final close of a $750,000 seed round. Since the initial announcement of the round earlier this month, Urban Us, the early-stage fund focused on companies transforming city life, has joined the syndicate comprised of Tech Square Labs and Knoll Ventures.
Cove.Tool software allows building designers and managers to plug in a variety of building conditions, energy options, and zoning specifications to get to the most cost-effective method of hitting building energy efficiency requirements (Cove.Tool Press Image / Cove.Tool / https://covetool.com).
In the US, the buildings we live and work in contribute more carbon emissions than any other sector. Governments across the country are now looking to improve energy consumption habits by implementing new building codes that set higher energy efficiency requirements for buildings.
However, figuring out the best ways to meet changing energy standards has become an increasingly difficult task for designers. For one, buildings are subject to differing federal, state and city codes that are all frequently updated and overlaid on one another. Therefore, the specific efficiency requirements for a building can be hard to understand, geographically unique and immensely variable from project to project.
Architects, engineers and contractors also have more options for managing energy consumption than ever before – equipped with tools like connected devices, real-time energy-management software and more-affordable renewable energy resources. And the effectiveness and cost of each resource are also impacted by variables distinct to each project and each location, such as local conditions, resource placement, and factors as specific as the amount of shade a building sees.
With designers and contractors facing countless resource combinations and weightings, Cove.Tool looks to make it easier to identify and implement the most cost-effective and efficient resource bundles that can be used to hit a building’s energy efficiency requirements.
Cove.Tool users begin by specifying a variety of project-specific inputs, which can include a vast amount of extremely granular detail around a building’s use, location, dimensions or otherwise. The software runs the inputs through a set of parametric energy models before spitting out the optimal resource combination under the set parameters.
For example, if a project is located on a site with heavy wind flow in a cold city, the platform might tell you to increase window size and spend on energy efficient wall installations, while reducing spending on HVAC systems. Along with its recommendations, Cove.Tool provides in-depth but fairly easy-to-understand graphical analyses that illustrate various aspects of a building’s energy performance under different scenarios and sensitivities.
Cove.Tool users can input granular project-specifics, such as shading from particular beams and facades, to get precise analyses around a building’s energy performance under different scenarios and sensitivities.
Traditionally, the design process for a building’s energy system can be quite painful for architecture and engineering firms.
An architect would send initial building designs to engineers, who then test out a variety of energy system scenarios over the course a few weeks. By the time the engineers are able to come back with an analysis, the architects have often made significant design changes, which then gets sent back to the engineers, forcing the energy plan to constantly be 1-to-3 months behind the rest of the building. This process can not only lead to less-efficient and more-expensive energy infrastructure, but the hectic back-and-forth can lead to longer project timelines, unexpected construction issues, delays and budget overruns.
Cove.Tool effectively looks to automate the process of “energy modeling.” The energy modeling looks to ease the pains of energy design in the same ways Building Information Modeling (BIM) has transformed architectural design and construction. Just as BIM creates predictive digital simulations that test all the design attributes of a project, energy modeling uses building specs, environmental conditions, and various other parameters to simulate a building’s energy efficiency, costs and footprint.
By using energy modeling, developers can optimize the design of the building’s energy system, adjust plans in real-time, and more effectively manage the construction of a building’s energy infrastructure. However, the expertise needed for energy modeling falls outside the comfort zones of many firms, who often have to outsource the task to expensive consultants.
The frustrations of energy system design and the complexities of energy modeling are ones the Cove.Tool team knows well. Patrick Chopson and Sandeep Ajuha, two of the company’s three co-founders, are former architects that worked as energy modeling consultants when they first began building out the Cove.Tool software.
After seeing their clients’ initial excitement over the ability to quickly analyze millions of combinations and instantly identify the ones that produce cost and energy savings, Patrick and Sandeep teamed up with CTO Daniel Chopson and focused full-time on building out a comprehensive automated solution that would allow firms to run energy modeling analysis without costly consultants, more quickly, and through an interface that would be easy enough for an architectural intern to use.
So far there seems to be serious demand for the product, with the company already boasting an impressive roster of customers that includes several of the country’s largest architecture firms, such as HGA, HKS and Cooper Carry. And the platform has delivered compelling results – for example, one residential developer was able to identify energy solutions that cost $2 million less than the building’s original model. With the funds from its seed round, Cove.Tool plans further enhance its sales effort while continuing to develop additional features for the platform.
The value proposition Cove.Tool hopes to offer is clear – the company wants to make it easier, faster and cheaper for firms to use innovative design processes that help identify the most cost-effective and energy-efficient solutions for their buildings, all while reducing the risks of redesign, delay and budget overruns.
Longer-term, the company hopes that it can help the building industry move towards more innovative project processes and more informed decision-making while making a serious dent in the fight against emissions.
“We want to change the way decisions are made. We want decisions to move away from being just intuition to become more data-driven.” The co-founders told TechCrunch.
“Ultimately we want to help stop climate change one building at a time. Stopping climate change is such a huge undertaking but if we can change the behavior of buildings it can be a bit easier. Architects and engineers are working hard but they need help and we need to change.”
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For many architects, the hardest part of their job starts after they finish designing a building, when the onerous process of code compliance begins. Written to ensure the safety and accessibility of buildings, codes dictate everything from the height and depth of stairs and where railings end, to the amount of floor space in front of toilets and the height of windows. Regulations are constantly updated, which means that even the most diligent team of architects often miss violations, resulting in costly delays. Y Combinator alum UpCodes wants to help them by using artificial intelligence, including natural language processing, to create what the San Francisco-based startup describes as “the spellcheck for buildings.”
Called UpCodes AI, the program is a plug-in that scans 3D models created with building information modeling (BIM) data and alerts architects about potential issues. It draws on the same backend as UpCodes’ first product, an app that compiles regulations into a constantly updated, searchable database with collaboration tools. UpCodes AI, which launched to the public last week, currently supports recent versions of Autodesk Revit and will add ARCHICAD, Sketchup and IFC in the future.
“This is like Grammarly for the construction industry. By highlighting code errors in real-time, the software acts as a code consultant working beside you at all times,” UpCodes co-founder and CEO Scott Reynolds tells TechCrunch.
UpCodes’ co-founders Garrett and Scott Reynolds and UpCodes AI technical lead Mark Vulfson
UpCodes was founded in 2016 after Reynolds became so frustrated by traditional code compliance while working as an architect that he switched career paths and launched the startup with his brother Garrett, a former software engineer at PlanGrid, to fix the process.
Building codes change so often that they are sometimes referred to as “living documents.” UpCodes’ database draws directly on regulations put online by municipalities and is updated almost in real-time. This eases a major pain point because many architects who thought they had followed regulations find out too late that they missed an amendment. In worst case scenarios, completed work needs to be torn out and rebuilt, potentially costing tens of thousands of dollars. This is a frequent occurrence and Scott Reynolds points to studies by McKinsey and the National Association of Home Builders that cite the complexity of code compliance as a major reason for reduced productivity in the construction industry and rising home prices.
Automating code compliance may also make it easier for architects to expand their practices, since regulations can vary dramatically between jurisdictions. UpCodes currently covers building codes in 26 states and the District of Columbia. Though UpCodes AI is still in its early stages, Reynolds tells TechCrunch that during its private beta it identified an average of about 27 violations per project.
One of its private beta users was Nicholas LoCicero, a designer with CallisonRTKL, an architecture firm known for retail design. LoCicero told TechCrunch in an email that the company used UpCodes AI on two retail locations that needed brand updates. Accessibility, which includes making sure that there are unobstructed ways of exiting a building from any point within it, is one of the most important parts of code compliance, and LoCicero said UpCodes AI was able to flag issues with door clearance, depth on stairs and tread width more quickly than the typical compliance process.
The program “definitely has the potential to save us hours of time with smart egress and accessibility tools and components that will help us develop projects faster during different phases of design” while ensuring that compliance is maintained, he added.

So far, UpCodes has raised $785,000 in funding from angel investors, as well as Y Combinator and Foundation Capital. It now has over 100,000 monthly active users and recently hired Mark Vulfson, former senior manager of engineering at PlanGrid, to serve as UpCodes AI’s technical lead.
Though the adoption of BIM data has made planning buildings more efficient, that’s “only a modest use of BIM’s full potential,” Reynolds says. He notes that it’s just within the past few years that more than 50% of American architecture firms have started using 3D information-rich modeling instead of 2D modeling. Programs like Revit and ARCHICAD, and new developments in APIs, finally made automated code compliance possible.
The use of AI in architecture is still new, but there are already several companies, including Autodesk and CoPlannery, exploring how to apply AI technologies to solve common problems in design, construction and engineering. Since AI is used in other major industries, including finance and healthcare, to automate compliance, it makes sense to assume that somewhere down the line, another company might try to build a competitor to UpCodes AI.
Reynolds believes that the UpCodes team’s combined industry and technical expertise will give it an edge over future rivals. He says his brother Garrett has a background in diffusion MRI analyzing large 4D data sets, while Vulfson brings “extensive experience deploying client side and web-based products” to the startup. UpCodes also works with a building code consultant who is based in New York City.
“The whole industry of code compliance has been neglected by software engineers for so long that it’s hard to imagine someone else doing what we’re doing,” Reynolds says.
“Building codes are a creativity killer. These regulations are one of the most restrictive components of design,” he adds. “Imagine restricting every brush stroke an artist makes with ten thousand rules–that’s what building codes feel like to an architect. That’s why I quit my career to do this. I want to take away that frustration and make architecture more fun, like it is in school.”
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