The rapid expansion of data centers and power infrastructure across the United States has created enormous demand for construction and development projects at scale. What is less discussed, however, is the dense web of regulatory requirements those projects must navigate - and how artificial intelligence is beginning to play a role in managing that burden.

A startup called Dili has positioned itself squarely at that intersection. The company announced on Thursday that it has closed a $15 million Series A funding round, following an earlier $6.7 million seed raise. Combined, the two rounds bring Dili's total capital to $21.7 million.

The Series A was led by Khosla Ventures, with additional backing from Allianz, Rebel Fund, Brick and Mortar Ventures' Darren Bechtel, and Y Combinator's Garry Tan. Dili previously participated in Y Combinator's Summer 2023 cohort.

Targeting the Compliance Complexity of Infrastructure Construction

While "AI for compliance" has become a familiar pitch in the startup world, Dili's focus is notably specific. The company targets the regulatory requirements tied to large-scale construction projects, particularly those receiving some form of federal funding. This is a niche area where the rules are numerous, frequently overlapping, and where the cost of getting things wrong can be severe.

Dili's co-founder and CEO Anand Chaturvedi cited Davis-Bacon Act regulations as a prime example. These rules grant the U.S. Department of Labor authority to establish prevailing wage requirements for workers on federally funded or assisted construction projects. Separately, clean energy projects funded through the Inflation Reduction Act are subject to their own prevailing wage and apprenticeship requirements, commonly referred to as PWA rules. Layered on top of those are varying obligations under OSHA and the EPA, depending on the type of work being performed.

The result is a regulatory environment that is difficult to track manually, especially across large projects with many contractors, subcontractors, and vendors. According to Chaturvedi, the financial consequences of falling short can be significant. "Non-compliance can result in millions of dollars of fines for those projects," he said. "So it's really powerful to be able to check all the information as it comes in, instead of just sampling data."

How the System Works

Given the high stakes involved, accuracy and reliability are paramount. Chaturvedi explained that Dili's technical architecture is deliberately designed to avoid the kinds of errors or unpredictable outputs that can arise from large language models when used without guardrails.

In Dili's system, AI models are applied only at the data ingestion layer - the stage where unstructured documents are processed and converted into structured, usable data. Once that conversion is complete, a deterministic rules engine takes over, applying the relevant compliance requirements in a consistent and predictable manner. Because the compliance rules themselves are complex but relatively static, this approach allows Dili to maintain accuracy without relying on probabilistic AI outputs at the point where precision matters most.

The practical impact of this workflow is considerable. Tasks that previously required a full day of manual review can now be completed within minutes. Chaturvedi described the capability in broader terms: "Imagine being able to read across the entire context of a company's internal documents, all of their vendors' documents, all of their ERP information, all of their payroll systems information, and then draw out the data that you need specifically for reporting or compliance."

Real-World Deployment and a Dual Business Model

Dili is not operating purely in the conceptual stage. Chaturvedi said the platform is currently active across approximately 700 projects, spanning a range of sectors including manufacturing facilities and data centers.

The company serves its customers through two distinct models. Roughly half of Dili's clients use the software directly as an internal tool, integrating it into their own compliance workflows. The other half outsource the compliance function entirely to Dili, which manages the process on their behalf in a contractor-style arrangement. Chaturvedi said the company is equipped to handle both approaches, though he expects the balance to shift over time.

In his view, the broader trend in professional services points toward software-driven internalization of tasks that were once handled by outside specialists. "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," he said. "The interesting thing will be how the market itself evolves and where the customer needs go as AI develops."

With a fresh round of funding and a growing project footprint, Dili is betting that the infrastructure buildout underway across the United States will continue to generate strong demand for tools that can keep pace with the regulatory complexity those projects bring with them.