AI for Private Equity: faster deal work and portfolio value creation
Common challenges
- Time-consuming manual research and document review
- Inconsistent quality of deal memos and analyses
- Difficulty quickly assessing portfolio company AI readiness
- Fragmented tools and workflows
Use cases
- Deal memo drafting assistant (with citations + guardrails)
- Market research summarization workflows
- Portfolio "AI readiness" assessment
- Operational playbooks: pricing, support, sales enablement agents
- Document processing: DD checklists, contracts, board packs
KPIs we impact
Analyst hours savedCycle time to ICPortfolio efficiency gains
Case studies
Deal WorkDocument ProcessingResearch
Deal Memo Assistant for Mid-Market PE
Nordic Capital Partners · Private equity firm (€500M AUM)
Analysts spent 60% of their time on research compilation and first-draft writing instead of analysis. Deal memo quality varied significantly between team members, and junior analysts often missed key risk factors.
40%
reduction in time-to-IC
3x
more deals screened per analyst
100%
citation compliance (audit requirement)
Portfolio ValueStrategyAssessment
Portfolio AI Readiness Assessment
Growth Equity Fund · Growth equity firm (12 portfolio companies)
The fund wanted to identify AI opportunities across their portfolio but lacked a systematic approach. Each company had different tech stacks, data maturity, and operational challenges.
8/12
companies launched AI initiatives within 6 months
€2.1M
estimated annual efficiency gains identified
4
shared AI vendors negotiated at portfolio level
Security & Compliance
- Deal data is extremely sensitive—local models often required
- Strict access control for AI assistants
- Documentation of all AI-generated analyses
- Guardrails to prevent hallucinated citations
- Separation between portfolio company data