The Problem: A mid-market private equity firm was being crippled by deal velocity. Their junior analysts—the engine of their deal team—were spending an average of 30-40 hours per deal on the mind-numbing "grunt work" of initial due diligence.

The manual process was a recipe for burnout and catastrophic errors:

• Manually combing through 200+ page Confidential Information Memorandums (CIMs) and data room files.

• Painstakingly copying and pasting revenue breakdowns, debt schedules, and operational data into complex Excel models.

• Building a preliminary LBO model from scratch, a process ripe for typos and formula errors that get discovered at midnight.

• Cross-referencing everything against broker notes and management presentations.

But the hidden cost was worse than the labor. The firm was losing out on competitive deals because their analysis was too slow. Junior talent was burning out, and the partners were making multi-million dollar decisions based on models that carried a high risk of "career-ending" manual errors.

We automated their entire due diligence data workflow.

The system now ingests any CIM, 10-K, or data room folder, uses AI to identify and extract over 50 key financial and operational KPIs (from historical EBITDA to customer concentration), validates the data against source documents, and pushes the clean, verified numbers directly into the firm's proprietary LBO model template in Excel.

We designed the system to meet the demands of high-stakes finance from day one. It provides radical transparency, with every extracted data point linking directly back to the source sentence or table in the original document. The AI is a "glass box," allowing analysts to audit the logic, not just trust a black box. The output is a fully functional Excel model, supercharging their existing workflow, not replacing it.

Result: The 30-40 hour manual data phase was reduced to under 30 minutes of AI processing and human review.

• 100% elimination of manual data entry errors in preliminary models.

• Analysts were freed from the "grunt work" to focus on high-level strategic analysis: assessing competitive moats, stress-testing assumptions, and finding the "real story" behind the numbers.

• The firm could now screen 5x more deals with the same team.

That's thousands of high-value analyst hours redirected from data entry to actual alpha generation.

The system paid for itself on the very first deal.