How Decathlon Capital streamlined deal diligence with F2

This case study describes how Decathlon Capital Partners (‘Decathlon’), a private credit investment firm focused on supporting growth-stage companies, used F2 to support diligence workflow.

The Firm has five active users across the investment team and uploaded 2,753+ file uploads generating 128 reports in the first four months. Key results are pre-screening reports and diligence packages that were generated in minutes vs. hours of manual work.

Decathlon has funded hundreds of growth-focused businesses over the past decade. The underwriting team evaluates a steady flow of opportunities – each involving large data rooms containing financial statements, term sheets, cap tables, customer information, and internal deal notes that are subsequently summarized into competitive analysis, financial summaries, cap table breakdowns, and diligence reports compiled from 90+ files per deal.

Before adopting F2, much of the work involved manual document review and synthesis. Team members often had to piece together company background, financial context, and diligence findings across many separate files before they could prepare internal materials.

When Decathlon deployed F2 in late 2025, the platform became embedded in their core deal workflow – from the first company name search through incorporation of key findings in final investment committee materials. What started as a tool for single-deal diligence is now expanding into other use cases across the portfolio – with Decathlon’s Managing Director describing the vision as moving “beyond using F2 for single-deal diligence and checklists” to becoming a central portfolio intelligence system as our usage and data set grows.

Decathlon’s main challenge was not the lack of information, but the effort required to review and organize it. Each deal generates a mountain of documentation – customer data, financial statements, cap table, term sheets, and investment recommendations – that must be synthesized into structured analysis before the team can make an investment decision.

This created a manual synthesis bottleneck: initial screening and full diligence packages required document-by-document review, while historical deal information was difficult to analyze and apply consistently across the portfolio. As a result, valuable insights from prior deals often remained buried in files and were not easily captured or used in a systematic way.

Decathlon needed a solution that could handle the full lifecycle – from initial pre-screening through active diligence and into portfolio monitoring – without adding headcount.

Decathlon rolled out F2 in stages. Starting with a V2 platform configuration session in November 2025, followed by rapid onboarding and a signed annual contract in late 2025.

Early use focused on pre-screening and company research. Over time, the platform was also used for fuller data room review, diligence reporting, and is currently expanding the scope to portfolio-level analysis.

Several additional use cases are also being considered, in part because reducing the time spent on manual tasks has created capacity for the team to explore ideas that they previously did not have the bandwidth to pursue. That has made it easier to test new, off-the-cuff concepts and determine whether they are worth developing further.

For new opportunities, team members used F2 to assemble initial company background and competitive context more quickly than they had through manual research alone.

These outputs were used as a starting point for internal evaluation, not as a substitute for underwriting judgment and were exported as PDFs for distribution to the deal team.

In addition to streamlining the initial screening process, the platform also produced supplemental materials that helped support early-stage screening discussions and provided context that was not typically compiled before F2 was adopted.

Once a company passed initial screening and the Investment Committee approved to enter the Diligence phase, the team used F2 to ingest larger diligence folders and generate structured summaries across financial, customer, and ownership materials. This reduced some of the repetitive work involved in turning raw files into diligence materials and became one of the platform’s most time-saving applications.

Typical outputs included reports highlighting potential data discrepancies across documents, as well as draft summaries of capital structure, customer concentration, financial performance, and key diligence considerations.

The platform’s AI tools also allowed the team to query the full data room and receive responses tied back to source documents, which made it easier to locate supporting information without manually searching through large volumes of files.

The team also began experimenting with portfolio-level analysis by loading historical term sheets, investment recommendations, and current portfolio performance metrics into the platform to explore whether patterns could be identified between current outcomes and the information available at the time of funding.

While certain deal structure data had already been captured in internal portfolio tracking systems, much of the more detailed narrative contained in the investment recommendations remained locked in standalone PDFs and was not available in an aggregated, searchable format across the portfolio.

This work is still in its early stages, but it has already given the team something they did not previously have: a unified, searchable view of historical deal activity at a more granular level.

The firm plans to continue refining this approach and, over time, may apply it on a recurring basis to compare portfolio performance against initial diligence findings.

The goal is to better identify patterns and indicators that could be helpful in future underwriting, both in recognizing potential risks and in surfacing positive signals that may not have been as clear during the original diligence process.

In February 2026, the platform was configured with a customized Diligence Checklist Template that allowed underwriters to quickly compare data room contents against required diligence items.

Previously, this was handled through a manual review of folders and subfolders, with items tracked separately on a checklist.

The updated workflow made it easier to monitor data room completion in one place, identify missing materials, and follow up with the company more efficiently before beginning a deeper diligence review.

F2 helped streamline two of the most time-consuming parts of Decathlon’s process — pre-screening and full diligence — with the biggest impact coming from faster diligence synthesis.

Based on internal feedback, the platform can reduce certain diligence tasks by roughly 25–50%, depending on the deal and the quality of source materials. Instead of manually extracting information document by document, the team can query full diligence packages through the AI Agent.

The platform supports a more consistent approach to gathering and drafting information across opportunities. While it isn’t directly attributable to investment outcomes, it meaningfully improves efficiency and consistency — freeing underwriters to spend more time on judgment-driven work like analysis, structuring, and IC preparation.

• Efficiency & Throughput Gains: Rather than replacing judgement, F2 reduced the amount of time spent assembling diligence materials from large data rooms. That allowed the team to move through early synthesis more efficiently and spend more of its time on interpretation, structuring, and decision support.
• Decision Quality & Investment Committee Readiness: By generating structured first-pass summaries across financial, customer, and ownership materials, the F2 platform supported a more consistent starting point for internal diligence work. This helped improve the quality and readiness of material used in Investment Committee discussions, while preserving the role of team review and underwriting judgement.
• Speed: Pre-screening reports and diligence packages that previously took hours of manual work could be produced in minutes. The ability to query the full data room and tie each response back to source documents further reduced the time spent searching across large file sets for supporting information.
• Institutional Knowledge: Historical term sheets, investment recommendations, and portfolio information could be brought into a unified, searchable environment. Without the F2 platform, doing this would have required a manual data-mining effort that the team did not have the bandwidth to undertake, making it much easier to revisit prior deal context and surface insights that had previously remained buried in standalone files.
• Portfolio Monitoring & Loan Performance: The team began exploring a loan performance project aimed at bringing ongoing portfolio financials and loan performance data into the F2 Platform. Over time, this could support more efficient monitoring, recurring dashboards, and a broader portfolio-level reporting.
• Exploratory Projects: As manual work has been reduced; the team has had more bandwidth to explore additional use cases beyond the original diligence workflow. That flexibility has made it easier to test new ideas, evaluate whether they have practical value, and expand the F2 platform into areas that previously would have been difficult to prioritize.

What began as a tool for screening individual deals has continued to expand into broader a platform for portfolio intelligence. The next phase of the expansion is already taking shape:

Portfolio Monitoring & Loan Performance – The team began exploring a “loan performance project” in January 2026 aimed at bringing ongoing portfolio company financials and loan performance data into the platform. The goal is to support more efficient portfolio monitoring, recurring dashboards, and a broader portfolio-level reporting.

Historical Deal Benchmarking – The firm is also considering restructuring existing deal workspaces, which could make it easier to benchmark new opportunities against historical portfolio companies across a wider range of metrics. Some of those metrics are already known, while other may emerge through continued use of the F2 platform as the team explores additional lines of analysis and determines which insights are realizable and useful enough to incorporate into future underwriting practices.

Investor Relations Reporting – As more fund-level information becomes centralized, the team is evaluating whether the platform could also support parts of the investor reporting process that have been historically manual and time-intensive.

Design Partner Status – Decathlon has been selected as a design partner for F2's upcoming Institutional Knowledge feature — alongside firms like Carlyle — reflecting the depth of their engagement and the strategic alignment between Decathlon's vision and F2's product roadmap .

For an investment firm reviewing complex opportunities and large diligence data rooms simultaneously, each with 90+ files of diligence materials, F2 didn't just speed up the existing workflow. It created an entirely new capability: the ability to turn years of accumulated deal history into actionable portfolio intelligence — and to do it in minutes instead of never.