Theresa Arevalo was in high school when she first tried finishing drywall at her brother's construction company. "It's a fine art," she says of mudding--applying and smoothing drywall. "Like frosting a cake, you have to give the illusion that the wall is flat." Fast-forward a few decades: Arevalo now works at Canvas, a company that's built a robot using artificial intelligence that's capable of drywalling with almost as much artistry as a skilled human worker. The robot has been deployed, under Arevalo's supervision, at several construction sites in recent months, including the new Harvey Milk Terminal at San Francisco International Airport and an office building connected to the Chase Center arena in San Francisco.

Construction sites are a massive jigsaw of people and parts that must be pieced together at the right time. With larger projects, delays become more expensive. McKinsey projects that on-site mismanagement costs the construction industry $1.6 trillion a year. But you might usually only have five managers overseeing construction of a building with 1,500 rooms, foresees Founder and CEO of British- Israeli startup Buildots Roy Danon. "There's no way an individual can control that much of detail." Mr. Danon thinks that artificial intelligence (AI) can help developing an image recognition system, which monitors every detail of an ongoing construction project.

Data-driven construction reporting company Buildots this week announced it has raised $16 million, a combination of a $3 million seed round and a $13 million series A. Cofounder Roy Danon says the funds will be used to scale and improve the company's products as Buildots expands to new regions around the world. Large construction projects -- which some countries have allowed to continue during the pandemic -- still rely on project managers to keep tedious manual records. These managers are often responsible for keeping tabs on countless tasks, in addition to tracking the progress of dozens (or more) contractors. Some analysts say the intractable logistical challenges lead 98% of large projects to suffer cost overruns of more than 30%. Making matters worse, 77% are estimated to be at least 40% late.