The Compliance Bottleneck in Infrastructure

Large-scale infrastructure projects, particularly those receiving federal funding, face a dense web of overlapping regulatory requirements. These include Davis-Bacon prevailing wage rules, OSHA safety standards, and EPA environmental mandates. Non-compliance carries significant financial risk, with potential fines reaching millions of dollars. Traditionally, managing this compliance has been a manual, time-intensive process involving the synthesis of disparate documents across ERP systems, payroll, and vendor contracts.

Hybrid Architecture for Reliability

Dili addresses this by separating AI processing from rule enforcement to ensure accuracy. The system uses LLMs exclusively in the data layer to ingest and structure unstructured documents. Once the data is structured, it is processed by a deterministic system that applies static compliance rules. This approach prevents the 'fuzziness' associated with generative AI from impacting the final compliance output, allowing the platform to reduce tasks that previously required a full day of manual labor to just a few minutes.

Market Adoption and Future Outlook

Currently deployed across approximately 700 projects—ranging from data centers to manufacturing facilities—Dili operates under two models: as an in-house software tool and as an outsourced contractor service. CEO Anand Chaturvedi anticipates a market shift toward the software-first model as AI continues to displace traditional professional services workflows. The company recently raised $21.7 million in total funding, including a $15 million Series A led by Khosla Ventures, to scale its operations.