AI startup Sapien has raised a new funding round led by Neo's Ali Partovi at a $180 million valuation, as the two-year-old company pushes beyond financial planning software into a broader system for analyzing how operational decisions affect a company's bottom line. Its customers now include Bayer, Carlex, Cooper Standard, Blink Charging, and Westgate Resorts.

The company's evolution is visible in how customers use the platform. According to a forthcoming case study reviewed by Fortune, Sapien rebuilt an existing profitability analysis for automotive supplier Carlex and found that factors the company had identified as contributing $10 million in positive EBITDA were actually producing a $2 million drag.

Sapien later uncovered an additional $1.5 million opportunity in a customer-channel pattern the Carlex team had not been looking for. The analysis took about 20 minutes.

"It took 20 minutes," said Jason Waltz, business unit VP of finance for Carlex's Aftermarket Division. "It would have probably taken us two weeks, and we probably wouldn't have gotten to that level."

This kind of investigation is increasingly the focus for Sapien, which founders Ron Nachum, Pranav Ravella, and Arya Grayeli launched in 2024 with an $8.7 million seed round led by General Catalyst. The company is part of a wave of startups applying large language models and AI agents to corporate finance work—territory long dominated by spreadsheet-based processes and tools like Anaplan, Workday Adaptive Planning, and Pigment—though Sapien is positioning itself around investigative analysis rather than planning and reporting.

The company has also grown quickly, with headcount increasing fivefold over the past year, bringing together AI researchers and engineers from Meta, Google, and Palantir alongside executives and operators from McKinsey & Company, Blackstone, Barclays, and Plaid. Nachum, Ravella, and Grayeli met in high school before attending Harvard, Stanford, and the University of Texas at Austin, respectively.

From FP&A to operating decisions

When Fortune first spoke with Nachum, who serves as CEO, two years ago, Sapien was focused on FP&A—financial planning and analysis, the finance function responsible for budgeting, forecasting, and explaining variances between plans and results. The company has since moved toward a broader question: not just what happened to a company's financial results, but what operational decisions caused them.

Nachum describes Sapien as a financial and operational system that connects the numbers in a company's financial statements with the underlying business. The idea is to help finance and operating teams investigate changes in revenue, margins, and cash flow, identify the drivers behind them, and then act on those findings.

That is a different proposition from adding another dashboard or automating another report. Sapien is betting that AI can do more of the investigative work traditionally handled by finance and operating teams.

Carlex has since expanded its use of Sapien into pricing, inventory, customer orders, OEM quoting, supply chain, and operations, Nachum said. Cooper Standard and Blink Charging are using the platform in similar ways, according to the case studies, with analyses that previously took hours or days being reduced to minutes and teams using the results to identify potential savings and margin improvements.

The trust factor

For Nachum, the biggest obstacle to AI adoption in finance isn't necessarily whether the technology can produce an answer.

"Every large company is data rich and analysis poor," he said. The harder part, he argues, is getting finance teams to trust the answer—whether the underlying numbers are correct, the analysis is reliable, and the company's data remains secure. It is a concern that extends beyond Sapien: hallucination risk and data governance remain widely cited barriers to enterprise adoption of generative AI, particularly in functions like finance where outputs feed decisions with direct financial consequences.

That makes trust a central part of Sapien's approach. Once teams become comfortable using the platform for financial analysis, Nachum said, its use can spread into functions such as supply chain, sales, and accounting.

The expansion also reflects Sapien's broader shift away from being an FP&A tool. Rather than treating finance as a standalone function, the company is trying to connect financial outcomes to the operational decisions that produce them.

One of Nachum's core bets has been to avoid turning the company into what he calls an "Excel copilot." The goal, instead, is to build a system that can investigate a business, find important patterns, and eventually help teams turn those findings into repeatable processes.

For Sapien, that is ultimately the bigger opportunity: using AI not simply to make existing financial work faster, but to find the operational decisions that can materially change a company's financial performance. How widely that approach spreads beyond early customers like Carlex and Cooper Standard will be a key measure of whether the company's new $180 million valuation holds up as it scales.

By Sheryl Estrada (Sheryl.Estrada@fortune.com). This story was originally featured on Fortune.com.