Dili raises $21.7 million to bring AI compliance to the infrastructure boom

Dili, an AI compliance startup, has raised $21.7 million in total funding, including a $15 million Series A round, to support infrastructure projects facing complex regulatory demands. The company, based in the United States, targets the growing need for compliance tools in the construction and energy sectors, especially as these industries expand alongside the rise of artificial intelligence. The latest funding brings Dili's cumulative capital to $21.7 million, combining its previous $6.7 million seed round with the newly secured Series A investment. The Series A round was led by Khosla Ventures, with additional backing from Allianz, Rebel Fund, Darren Bechtel of Brick and Mortar Ventures, and Garry Tan of Y Combinator. Dili had previously participated in Y Combinator’s Summer 2023 program, indicating early-stage validation of its business model and technology. The company's mission centers around helping infrastructure developers navigate the intricate web of federal regulations that govern large-scale construction projects. One of the key challenges Dili addresses is the application of the Davis-Bacon Act, which mandates prevailing wages for federally funded construction projects. Additionally, the Inflation Reduction Act introduces specific prevailing wage and apprenticeship rules for clean energy initiatives, further complicating compliance. Other relevant regulations include those enforced by the Occupational Safety and Health Administration (OSHA) and the Environmental Protection Agency (EPA). These rules vary depending on the type of work performed, creating a layered compliance landscape that traditional methods struggle to manage effectively. According to Dili's co-founder and CEO, Anand Chaturvedi, non-compliance can lead to substantial financial penalties, potentially reaching millions of dollars. To mitigate this risk, Dili employs an AI-driven approach that integrates unstructured data, such as internal company documents, vendor records, ERP systems, and payroll information, into a structured format. This allows for real-time analysis against static compliance rules, significantly reducing the time required for compliance checks. Tasks that once took an entire day can now be completed in minutes, enhancing efficiency and accuracy. Chaturvedi emphasizes that contemporary AI models are only utilized in the initial phase of data processing, where they convert raw, unstructured documents into usable data. Once this transformation occurs, a deterministic system applies the necessary compliance checks. This hybrid approach ensures that the final output remains free from the ambiguities often associated with large language models. By separating AI functions from the decision-making process, Dili aims to maintain precision and reliability in its compliance solutions. Currently, Dili's software is operational across approximately 700 projects, spanning diverse sectors such as manufacturing facilities and data centers. Of these, roughly half are utilizing the platform internally as an in-house tool, while the remaining half rely on external contractors to manage compliance tasks. Despite this current distribution, Chaturvedi predicts a future shift toward greater adoption of in-house software solutions. As AI continues to evolve, he anticipates that more organizations will integrate compliance tools directly into their operations, streamlining workflows and reducing dependency on third-party services. Looking ahead, Dili is positioned to benefit from the increasing demand for automated compliance solutions in the infrastructure sector. With ongoing advancements in AI and expanding regulatory frameworks, the company's ability to adapt and refine its offerings will likely determine its long-term success in this rapidly evolving market.