The rapid expansion of AI infrastructure is bringing a wave of new data centers and power projects across the United States. But behind the scenes, these projects face an increasingly complex web of compliance regulations. A new company called Dili is stepping in to apply artificial intelligence to that challenge, announcing $21.7 million in total funding to scale its platform.
On Thursday, Dili revealed it had raised $15 million in Series A funding, on top of a $6.7 million seed round. The round was led by Khosla Ventures, with participation from Allianz, Rebel Fund, Brick and Mortar Ventures’ Darren Bechtel, and Y Combinator’s Garry Tan. Dili was previously part of Y Combinator’s Summer 2023 batch.
Targeting the Infrastructure Boom
The United States is in the middle of a once-in-a-generation infrastructure buildout. Massive investments in semiconductor manufacturing, clean energy, electric vehicle production, and data centers are reshaping the industrial landscape. Government programs like the Inflation Reduction Act and the Bipartisan Infrastructure Law have injected hundreds of billions of dollars into new projects, creating a surge of construction activity.
But with federal money comes federal oversight. Every federally funded construction project must comply with a dense matrix of labor, environmental, and safety regulations. This is where Dili sees its opportunity. The company’s platform is designed specifically to handle compliance for construction projects, particularly those receiving government support.
Navigating Complex Regulations
The regulatory environment for infrastructure projects is daunting. Dili’s co-founder and CEO, Anand Chaturvedi, points to the Davis-Bacon Act as a prime example. Under Davis-Bacon rules, the Department of Labor sets prevailing wages for workers on federally funded projects. Contractors must ensure they pay these wages, keep detailed records, and submit certified payroll reports.
For clean energy projects funded under the Inflation Reduction Act, there is an additional set of prevailing wage and apprenticeship rules, often called PWA rules. These require contractors to pay prevailing wages and employ registered apprentices for a certain percentage of labor hours. If a project fails to meet these requirements, the penalties can be severe. In some cases, the tax credit benefits under the IRA can be reduced or eliminated entirely.
On top of that, projects must contend with OSHA workplace safety standards, EPA environmental regulations, and various state and local rules. The overlapping nature of these requirements makes compliance a major headache for project managers. Even small mistakes in documentation can lead to hefty fines or legal disputes.
The High Cost of Non-Compliance
Chaturvedi explains that the financial stakes are enormous. “Non-compliance can result in millions of dollars of fines for those projects,” he says. “So it’s really powerful to be able to check all the information as it comes in, instead of just sampling data.”
Traditional compliance processes rely on manual reviews. Teams of lawyers, accountants, and compliance officers sift through invoices, payroll records, timesheets, and subcontractor documents. This is slow, expensive, and prone to human error. With thousands of data points across hundreds of workers and dozens of subcontractors, it is easy to miss a discrepancy.
Dili’s approach is to automate much of this process using AI, but with a critical twist to ensure reliability.
AI and Deterministic Systems
Many startups pitch “AI for compliance,” but Dili uses a hybrid architecture designed to avoid the hallucinations and unpredictability often associated with large language models. Contemporary AI models are used only in the data layer of Dili’s system. This is the engine that takes unstructured documents, such as PDFs, emails, and spreadsheets, and translates them into structured data.
Once the data is extracted, a deterministic system takes over. The compliance rules themselves are complex but static. They do not change from one document to the next. This deterministic engine sorts the data according to those fixed rules, ensuring that the final output is consistent and auditable. The AI does the heavy lifting of understanding messy human-generated documents, while the deterministic layer applies the law with precision.
According to Chaturvedi, this approach delivers dramatic efficiency gains. A task that used to take a full day’s work can now be dispatched in a matter of minutes. For project managers, that means faster payroll approvals, quicker reporting, and fewer compliance bottlenecks.
Reading Across the Entire Company
Chaturvedi describes the capability as “reading 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 drawing out the data that you need specifically for reporting or compliance.”
This holistic view is essential because compliance is not just about individual documents. It requires cross-referencing payroll records with contract terms, comparing subcontractor certifications with project schedules, and verifying that all hiring practices meet apprenticeship requirements. Dili’s platform consolidates these disparate data sources into a single, coherent picture.
The software is already working in real-world conditions. Chaturvedi says Dili is currently being used on “about 700 projects,” ranging from manufacturing facilities to data centers. This early adoption shows that the market is hungry for a more efficient compliance solution.
Software as a Service and Contractor Models
One notable aspect of Dili’s business is how customers are using the product. Roughly half of the projects are using Dili as an in-house software tool, where the customer’s own team runs the platform. The other half outsource the entire compliance process to Dili on a contractor model.
This flexibility allows Dili to serve a range of clients. Some large construction firms have teams that can absorb new software quickly. Others, especially smaller subcontractors, prefer to offload the responsibility entirely. Dili is able to handle both types of contracts, although Chaturvedi expects the industry to shift increasingly toward the software model.
“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 says. “The interesting thing will be how the market itself evolves and where the customer needs go as AI develops.”
The Role of Venture Backing
The new funding will help Dili scale its engineering team, expand its sales efforts, and enhance its platform for new types of infrastructure projects. Khosla Ventures has a strong track record of backing transformative AI companies, and its lead role in this round signals confidence in Dili’s approach.
Other investors bring specialized expertise. Allianz, the global financial services company, has deep knowledge of risk management and insurance. Brick and Mortar Ventures focuses on the built environment, while Rebel Fund and Garry Tan are closely tied to Y Combinator’s startup ecosystem. This combination of fintech, construction, and startup experience will be valuable as Dili navigates the growing infrastructure market.
The infrastructure boom is not showing any signs of slowing. Data centers are being built at record pace to support AI workloads, and the energy sector is undergoing a massive transition to cleaner sources. Each new project brings its own compliance challenges, and Dili is positioning itself to be the go-to platform for managing that complexity.
In the coming years, the demand for accountable and efficient compliance solutions is likely to grow. Federal regulations will continue to evolve, and project owners will need technology to keep up. Dili’s combination of AI-driven data extraction and deterministic rule enforcement could become a model for how the industry handles regulation in the age of AI. For now, the company is focused on executing its vision across hundreds of active projects, proving that compliance can be both fast and reliable.
Source: TechCrunch News