Dili Raises $15M Series A to Automate Wage Monitoring and Payroll Compliance With AI

Dili Raises $15M Series A to Automate Wage Monitoring and Payroll Compliance With AI

For decades, the way America's biggest construction and energy projects proved they paid workers fairly came down to a hopeful ritual: an auditor pulled roughly 10% of the payroll data, spent six months to two years poring over it, and delivered findings long after the money had moved. Dili, a New York-based startup, is betting that generative AI can replace the sampling with something closer to total surveillance of the paperwork. On July 30, 2026, the company said it had raised a $15 million Series A led by Khosla Ventures, capital aimed squarely at automating one of the least glamorous and most litigated corners of the back office: prevailing-wage and certified-payroll compliance.

The Round

The Series A was led by Khosla Ventures, with participation from Y Combinator's Garry Tan, the insurer Allianz, Brick and Mortar Ventures' Darren Bechtel, and Rebel Fund. It follows a $6.7 million seed round and brings Dili's total funding to $21.7 million. The company plans to spend the money hiring across engineering, product, and go-to-market.

Dili was co-founded in 2023 by CEO Anand Chaturvedi and CTO Brian Fernandez, both alumni of Coinbase. Chaturvedi previously built products at the crypto exchange tied to more than $50 million in revenue, conducted machine-learning research at Apple, and was a Kleiner Perkins Fellow; Fernandez led engineering on core retail infrastructure at Coinbase. Chaturvedi has said he started the company after seeing how much high-stakes audit and diligence work "still ran through email and spreadsheets, even with millions of dollars at stake."

What Dili Actually Does

The product targets a specific regulatory thicket. Federally funded and clean-energy projects in the U.S. must comply with Davis-Bacon prevailing-wage rules and apprenticeship requirements to keep their funding and tax credits. Getting it wrong is expensive: fines, clawbacks, and lost investment tax credits can run into the millions per project. Compliance work has traditionally meant certified payroll reports, wage determinations, and audit trails, most of it reviewed by hand or outsourced to Big Four consultants like KPMG, EY, PwC, and Deloitte.

Dili's pitch is coverage. Instead of sampling around 10% of the data, its AI reviews 100% of it in real time, checking certified payroll, wage determinations, apprenticeship ratios, documents, and exceptions as they come in. According to the company, it has processed more than $1.4 billion in gross wages, 5.2 million labor hours, and nearly 16,000 certified payroll reports across 700-plus projects, cutting weekly review time from more than seven hours to under five minutes per organization. Dili says it has caught or prevented more than $50 million in fines and clawbacks, including $6 million in IRS penalty exposure for a single customer before it became a liability, and protected over $1 billion in funding overall. Named customers include EDF, Radiance, Heelstone, and Borea.

"Compliance in this industry has always meant hoping the sample your auditor pulled happens to be clean," Chaturvedi said. "We look at everything, every report, every wage determination, every week. The first time we ran a look-back on a customer's historical data, we found in four days what would have taken their consultants months to find by sampling, if they'd found it at all."

Why Regulated Payroll Is Suddenly Hot

Dili's raise is a clean example of a broader shift: from AI novelty to AI utility. The buzz around chatbots and image generators is giving way to vertical AI "agents" pointed at narrow, rules-heavy back-office work — the kind of tasks that are tedious, expensive to staff, and unforgiving of error. Wage and payroll compliance checks nearly every box that makes such work attractive to build a company around.

The rules are dense but deterministic, which suits AI that can read documents and flag deviations against a known standard. The cost of a mistake is concrete and large, so buyers can quantify the return on avoiding a single clawback. And the incumbent process — periodic sampling by human auditors — is slow enough that "we check everything, continuously" is a genuine product differentiator rather than a marketing line. Crucially, the timing rides a wave of federal infrastructure and clean-energy spending, which has multiplied the number of projects subject to prevailing-wage rules while the pool of specialists who understand them stays thin.

Investors framed the opportunity in exactly those terms. "America is in the middle of the largest infrastructure buildout in a generation. One missed financial compliance requirement puts hundreds of millions of dollars at risk," said Vinod Khosla, founder of Khosla Ventures. "Dili gives the industries building this new era of infrastructure a real-time, AI-powered assurance layer that catches problems before they become liabilities." The presence of Allianz, an insurer with a direct interest in quantifiable risk, and Brick and Mortar Ventures, a construction-tech specialist, signals that the appeal runs beyond generalist venture enthusiasm.

What to Watch

The obvious question is whether Dili stays a compliance tool or becomes a wedge into the far larger market for audit and assurance work now handled by consultants. The company has said it intends to expand "beyond prevailing wage and apprenticeship compliance into broader audit and waste detection, the same work traditionally outsourced to Big Four consultants" — an ambition that pits a 2023 startup against firms with decades of institutional trust and regulatory relationships.

Two things will determine whether that works. The first is accuracy under scrutiny: AI that reads payroll and vouches for compliance is only useful if regulators, auditors, and insurers accept its findings, which raises the bar well above a helpful summary. The second is durability of the moat. If checking 100% of the data becomes table stakes, the winners will be the platforms that own the customer relationship and the historical data, not just the model. For now, Dili has a fast-growing category, marquee backers, and a pitch that lands in a sentence — replace the sample with everything. The next year will show whether regulated back-office AI is a feature or a franchise.