Mid-Market PE Firm Cuts Initial Deal Review ~50% With Four AI Agents

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Four integrated AI agents automated origination, CIM analysis, divestiture scanning, and data-room review.

~50% faster review

< 4 weeks

Implementation Time

Brian Benedict

Co-Founder & CCO

Eliza

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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.

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, and public sources such as SEC filings, earnings releases, and transcripts

Integration Points

Four agents embedded in existing tools: teaser intake from email with metadata to Salesforce and Excel, CIM financials extracted into structured Excel, continuous scanning of public filings and news, and 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

Technology Utilized

Implementation Complexity

Time Savings

Headcount Avoidance

Best Fit For

Mid-market private equity firms wanting to automate origination-through-diligence workflows and expand deal capacity without adding headcount.

Brian Benedict

Co-Founder & CCO

Eliza

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.

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Industry:

Financial Services

Business Function:

Operations

Executive & Strategy

Project Cost:

Cost not disclosed

Organization Type:

Private Equity Firm

AI Pattern:

Process Automation (RPA + AI)

Document Processing & Extraction

Decision Support & Scoring

Value Type:

Time Savings

Headcount Avoidance

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.

Originally published by

Eliza