Scaling private markets research through AI-powered automation

A US-based investment firm, focused on private equity investments, sought to enhance private markets research workflows through automation to improve sourcing coverage, diligence efficiency, and depth of company and sector analysis.

• Manual, time-intensive workflows led to delays, inconsistencies, a higher risk of errors and scalability issues
• Limited bandwidth across investment and research teams to support increasing research needs
• Fragmented data across internal systems, external databases and public sources
• Lack of scalable analytics infrastructure for end-to-end automation, large datasets and real-time tracking

Sourcing:

• Built workflows to source, clean and analyze government and thirdparty datasets to identify attractive market opportunities
• Automated monitoring of news, funding activity, customer wins and hiring trends to surface sourcing signals and deal leads

Initial screening/meeting preparation:

• Prepared AI- and FactSet-enabled company briefs, covering business profile, financials, management, ownership history, competitors and investors

Due diligence:

• Developed CIM comparison agents to identify changes in narrative, KPIs, risk language, positioning and investment case
• Summarized expert calls and public peer commentary into diligenceready takeaways on market growth, competitive dynamics and risk implications

Portfolio monitoring:

• Built automated trackers to refresh KPIs, operating metrics and peer benchmarks, reducing manual work and improving portfolio review consistency
• Set up structured company and sector monitoring to flag material developments