Dili Secures $21.7M to Power AI Compliance in Infrastructure Boom

The expansion of artificial intelligence necessitates substantial new data center and power infrastructure. Intriguingly, these very infrastructure projects may themselves be significantly aided by AI technologies.

This Thursday marked a significant development with Dili, an emerging AI compliance firm, announcing a $15 million Series A funding round. This capital is specifically earmarked for the burgeoning array of U.S. infrastructure initiatives. This latest infusion of funds follows a prior $6.7 million seed round, elevating the company's total capital raised to an impressive $21.7 million.

The Series A round saw leadership from Khosla Ventures, with additional participation from notable investors including Allianz, Rebel Fund, Darren Bechtel of Brick and Mortar Ventures, and Garry Tan from Y Combinator. Prior to this, Dili was a participant in Y Combinator's Summer 2023 cohort.

While "AI for compliance" is a prevalent concept among startups, Dili distinguishes itself by concentrating on the intricate web of regulations governing construction projects, particularly those receiving federal funding. Anand Chaturvedi, Dili's co-founder and CEO, provided the Davis-Bacon rules as a prime example, which empower the Department of Labor to establish prevailing wages for specific projects. Furthermore, distinct prevailing wage and apprenticeship (PWA) rules apply to clean energy projects financed through the Inflation Reduction Act (IRA), alongside various OSHA or EPA regulations that come into play based on the specific scope of work.

This intricate landscape of overlapping requirements means that even minor errors can incur significant financial penalties. "Non-compliance can result in millions of dollars of fines for those projects," Chaturvedi emphasized. He added, "So it’s really powerful to be able to check all the information as it comes in, instead of just sampling data."

With such high stakes involved, reliability stands as a paramount concern. Chaturvedi, however, expressed confidence that Dili's unique architectural design effectively prevents any potential "fuzziness" stemming from large language models (LLMs) from impacting the final output. The company strategically employs contemporary AI models exclusively within its data layer, which functions as the engine for transforming unstructured documents into organized, structured data. Following this, a deterministic system meticulously sorts and processes this data in accordance with the complex, yet static, compliance regulations. When operating optimally, a task that once demanded a full day's effort can now be accomplished in mere minutes.

Chaturvedi vividly described the system's capability: "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."

This sophisticated system is already demonstrating its practical efficacy. Chaturvedi confirmed that Dili’s software is currently deployed across "about 700 projects," encompassing a diverse range from manufacturing facilities to critical data centers.

Significantly, Chaturvedi noted that approximately half of these projects leverage Dili as an in-house software tool, while the remaining half opt to outsource the entire compliance process through a contractor model. Dili is equipped to facilitate both contractual approaches, though Chaturvedi foresees a future industry trend shifting increasingly towards the direct software model.

Chaturvedi articulated his vision, stating, "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 concluded, "The interesting thing will be how the market itself evolves and where the customer needs go as AI develops."