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Mid-Market PE Firm Cuts Initial Deal Review ~50% With Four AI Agents
Four integrated AI agents automated origination, CIM analysis, divestiture scanning, and data-room review.
~50% faster review
< 4 weeks
Implementation Time
Not disclosed
Project Cost
the challenge
BD teams manually triaged thousands of brief teasers in slow, error-prone work; analysts spent hours extracting tables from CIMs and rebuilding models; sourcing teams manually scanned filings for divestitures; and diligence teams reviewed large data rooms by hand, elongating deal cycles.
what they built
Eliza deployed four integrated AI agents: a deal-flow origination agent that classifies and flags teasers, a CIM analysis agent that extracts financials into Excel and flags diligence issues, a corporate divestitures agent that scans SEC filings and transcripts, and a data-room agent that searches documents and summarizes risk.
Agents were embedded into existing workflows, email intake, BD pipelines, Excel modeling, Salesforce tracking, and data-room platforms, with minimal change management, delivering first value in two weeks.
best fit for
Mid-market private equity firms wanting to automate origination-through-diligence workflows and expand deal capacity without adding headcount.
Ai ROLE
Four AI agents handle origination triage, CIM analysis, divestiture scanning, and data-room review, surfacing and structuring information while the deal team decides.
infrastructure
- Email for deal teaser intake
- Salesforce for pipeline tracking
- Excel for financial modeling
- Data room platforms for diligence
- SEC filings
- Earnings releases
- Transcripts
integration points
- Teaser intake from email with metadata to Salesforce and Excel
- CIM financials extracted into structured Excel
- Continuous scanning of public filings and news
- Data-room search within existing diligence workflows
impact
~50% faster
Teaser triage cut ~50% (saved 3-4 hrs/batch)
CIM 30-40%
CIM analysis 30-40% faster; doc review down 20-30%
Pipeline +15%
Divestiture scanning surfaced 5-10 carve-outs/quarter, no headcount added
Brian Benedict
Co-founder of Eliza, a boutique AI transformation firm and OpenAI Advanced Tier Partner. A two-time founder and former Hugging Face, he helps enterprises put AI to work through agentic engineering.
Get an intro
Talk to this teamindustry
Financial Services
business organization
Operations
Executive & Strategy
AI TYpe
Process Automation (RPA + AI)
Document Processing & Extraction
Decision Support & Scoring
value type
Time Savings
Headcount Avoidance
more from this expert
frequently asked questions
How did Chariot Capital cut initial deal review by about 50% with AI agents?
The experts deployed four integrated AI agents for origination, CIM analysis, divestiture scanning, and data room review, embedded in existing email, Salesforce, and Excel workflows. Initial deal review fell roughly 50 percent.
What AI tools and approach did Chariot Capital use?
The solution uses four AI agents in a decision support and automation approach: a deal flow origination agent, a CIM analysis agent that extracts financials into Excel, a corporate divestitures agent that scans SEC filings and transcripts, and a data room agent that searches documents and summarizes risk.
What results did Chariot Capital achieve?
Initial deal review fell roughly 50 percent and the pipeline expanded about 15 percent without added headcount.
How long did it take to see results?
The agents were embedded into existing workflows with minimal change management, delivering first value in two weeks.
Who is this deal automation approach best for?
Mid market private equity and deal teams that manually triage teasers, rebuild models from CIMs, and review large data rooms.
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