The wave of new data centers and power infrastructure required to support artificial intelligence is creating a parallel demand: AI tools to manage the complex compliance rules governing those construction projects. On Thursday, a startup called Dili announced it has raised $15 million in Series A funding, bringing its total capital raised to $21.7 million, to address exactly that need.
The Series A round was led by Khosla Ventures, with participation from Allianz, Rebel Fund, Darren Bechtel of Brick and Mortar Ventures, and Y Combinator’s Garry Tan. Dili, which was part of Y Combinator’s Summer 2023 batch, previously raised a $6.7 million seed round.
Also read: Fish Audio raises $50M seed to build expressive AI voice models for creators and enterprises
Targeting the federal funding compliance tangle
While “AI for compliance” is a common pitch among startups, Dili focuses on a specific and particularly thorny area: the overlapping federal, state, and local regulations that apply to construction projects—especially those receiving federal funding. Co-founder and CEO Anand Chaturvedi points to the Davis-Bacon Act, which allows the Department of Labor to set prevailing wages on certain federally funded projects, as a prime example. Separately, clean energy projects funded under the Inflation Reduction Act (IRA) must comply with prevailing wage and apprenticeship (PWA) rules, while OSHA and EPA regulations add additional layers depending on the work type.
“Non-compliance can result in millions of dollars of fines for those projects,” Chaturvedi explains. “So it’s really powerful to be able to check all the information as it comes in, instead of just sampling data.”
Also read: US Grid Operator Will Cut Power to Large Data Centers to Prevent Blackouts
Given those high stakes, reliability is a central concern. Chaturvedi says Dili’s architecture prevents the kind of “fuzziness” that large language models can introduce. Contemporary AI models are used only in the company’s data layer, where they convert unstructured documents—internal reports, vendor documents, ERP data, payroll information—into structured data. From there, a deterministic system applies the complex but static compliance rules. When it works, a task that once took a full day can be completed in minutes.
Already deployed across 700 projects
Dili’s software is already being used on about 700 projects, ranging from manufacturing facilities to data centers. Chaturvedi notes that roughly half of those projects use Dili as an in-house software tool, while the other half outsource the entire compliance process on a contractor model. He anticipates the industry will shift more toward the software model as AI capabilities mature.
“Software and AI are going to start eating a lot of those professional services workflows, so I think more and more people will start to bring those in house,” Chaturvedi says. “The interesting thing will be how the market itself evolves and where the customer needs go as AI develops.”
The funding arrives as the US faces an infrastructure boom driven by the CHIPS Act, the IRA, and massive private investment in data centers. For project owners and contractors, the ability to automate compliance checks could mean the difference between staying on budget and facing costly penalties. Dili’s approach—using AI for data extraction while relying on deterministic logic for rule enforcement—may offer a template for how AI can be deployed in high-stakes regulatory environments without sacrificing accuracy.
Be the first to comment