As the U.S. pushes to build more data centers and clean energy infrastructure, a new wave of compliance challenges has emerged. Dili, an AI-driven compliance company, announced Thursday that it has raised $15 million in Series A funding, bringing its total funding to $21.7 million. The company is focused on helping infrastructure projects navigate the dense web of federal and state regulations.
Funding details
The Series A round was led by Khosla Ventures, with participation from Allianz, Rebel Fund, Darren Bechtel of Brick and Mortar Ventures, and Garry Tan of Y Combinator. Dili was part of Y Combinator's Summer 2023 batch, which gave it early access to a network of investors and enterprise customers. The new funding follows a $6.7 million seed round, meaning the startup has now raised $21.7 million in total.
The announcement comes at a time when infrastructure spending is surging. The Bipartisan Infrastructure Law and the Inflation Reduction Act have unlocked hundreds of billions of dollars for new projects, but they also come with strings attached. Many of those projects require compliance with wage, apprenticeship, environmental, and safety rules that are notoriously difficult to track across multiple jurisdictions.
What Dili does
Dili's platform is designed for construction projects that receive federal funding or must comply with federal standards. The company focuses on rules that are often overlooked but can carry severe penalties. For example, Davis-Bacon rules allow the Department of Labor to set prevailing wages for certain projects. A separate set of prevailing wage and apprenticeship rules, often called PWA rules, applies to clean energy projects funded under the IRA. Depending on the project type, OSHA and EPA regulations also come into play.
The combination of these overlapping requirements can be overwhelming for project managers, contractors, and compliance officers. Even minor mistakes can lead to millions of dollars in fines and delays. "Non-compliance can result in millions of dollars of fines for those projects," said Anand Chaturvedi, Dili's co-founder and CEO. "So it's really powerful to be able to check all the information as it comes in, instead of just sampling data."
The platform uses contemporary AI models in its data layer to transform unstructured documents into structured data. These models read contracts, vendor agreements, payroll systems, and ERP data, pulling out the relevant information needed for compliance reporting. Once the data is extracted, a deterministic system applies the complex but static compliance rules. This two-step architecture ensures that the AI's flexibility does not introduce errors into the final compliance assessment.
Chaturvedi explained that the system can read across the entire context of a company's internal documents, vendor documents, ERP information, and payroll systems, then draw out the specific data needed for reporting or compliance. "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, you know, reporting or compliance," he said.
Why compliance is a growing bottleneck
The infrastructure boom has created an urgent need for faster and more reliable compliance processes. Traditional approaches often involve teams of lawyers and consultants manually reviewing documents and sampling data. This is slow, expensive, and prone to errors, especially when a project involves many subcontractors and changing requirements.
Data centers, in particular, are being built at an unprecedented pace to support AI workloads. These facilities require massive amounts of power and cooling, which means new substations, transmission lines, and water systems. Each of these components may come with its own set of regulatory requirements, and the complexity increases when projects span multiple states or use federal funds.
The boom has also drawn attention from policymakers. Some lawmakers have called for stricter oversight of the construction industry, especially around wage protections and environmental standards. This makes compliance a top priority for project owners and general contractors, who need to demonstrate that they are following the rules.
Hybrid adoption model
Dili is already being used on approximately 700 projects, according to Chaturvedi. These range from manufacturing facilities to data centers. Notably, the company sees two distinct patterns of adoption. About half of its customers use Dili as an in-house software tool, integrating it into their existing workflows. The other half outsource the entire compliance process to Dili, essentially using the company as a contractor that manages compliance on their behalf.
Dili supports both models, but Chaturvedi believes the market will gradually shift 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 said. "The interesting thing will be how the market itself evolves and where the customer needs go as AI develops."
This shift is likely because in-house software offers more control, scalability, and cost predictability over time. It also allows companies to accumulate historical compliance data, which can be useful for future projects. Outsourcing remains attractive for smaller organizations that lack the internal capacity to run such systems.
The role of AI in regulated industries
The phrase "AI for compliance" has become common in the startup world, but the challenges are far from uniform. Many compliance platforms focus on financial services or healthcare, where the rules are more standardized and the data is often digital. Construction compliance, by contrast, requires interpreting a patchwork of federal, state, and local rules, each with its own exceptions and updates.
Dili's approach highlights a broader trend of using AI to handle unstructured documents in heavily regulated industries. By combining machine learning with deterministic logic, the company can provide high reliability while still automating a large portion of the work. This is particularly important in an environment where mistakes are costly and regulators are increasingly using advanced data analytics to detect non-compliance.
The company's architecture is designed to prevent LLM-based fuzziness from sneaking into the final product. AI models are only used for the initial extraction of structured data from documents. After that, a deterministic system applies the rules, ensuring that the output is consistent and auditable. This separation of concerns is essential for building trust with customers and regulators.
Investment context and market potential
The new funding round also reflects a broader investor interest in AI-powered vertical software. As the infrastructure boom accelerates, many venture capital firms are looking for startups that can reduce the cost and complexity of compliance. Khosla Ventures' participation is notable because the firm has a history of backing frontier technology companies, including OpenAI and other AI-focused startups.
Dili's Y Combinator pedigree also gives it access to a wide network of founders and product talent. The company's ability to grow from a seed-stage startup to a platform used on hundreds of projects within a short period demonstrates a strong product-market fit.
The market for construction compliance software is still emerging, but it is growing quickly. With federal spending on infrastructure expected to continue, and with public attention on worker protections and environmental review processes, the need for automated compliance tools will likely increase.
Future outlook
Chaturvedi says Dili will use the new capital to expand its engineering team, improve its AI models, and grow its customer success organization. The company also plans to deepen its coverage of specific regulatory domains, from Davis-Bacon to the Inflation Reduction Act's many requirements.
The next few years will likely bring more infrastructure projects, more data centers, and more regulatory scrutiny. For Dili, that means more demand for its services and more opportunities to replace manual compliance workflows with automated systems.
"The interesting thing will be how the market itself evolves and where the customer needs go as AI develops," Chaturvedi said. "We're building to meet those needs head-on."
Source:TechCrunch News