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AI diligence agents for private equity

Know what could break the deal before you buy the company.

Keystone verifies management claims, investigates discrepancies and surfaces the financial, customer and contract risks that could change your investment decision.

Built for private equity deal teams conducting high-stakes diligence.

Management Claim Verification Revenue Quality Customer Retention Analysis Customer Concentration EBITDA Add-Back Review Contract Diligence Forecast Challenge Management Q&A Source-Linked Evidence Investment Committee Preparation Management Claim Verification Revenue Quality Customer Retention Analysis Customer Concentration EBITDA Add-Back Review Contract Diligence Forecast Challenge Management Q&A Source-Linked Evidence Investment Committee Preparation

The problem

Private equity teams have the data. They do not always have the truth.

During diligence, deal teams receive CIMs, financial statements, customer files, contracts and thousands of data-room documents. Keystone helps teams verify what is real, identify what does not add up and focus diligence on the issues that could change the deal.

01

Conflicting numbers

Revenue, retention, EBITDA and customer metrics often do not reconcile across source files.

02

Unsupported claims

Management narratives can sound convincing before the underlying evidence has been tested.

03

Manual investigation

Associates repeatedly clean files, compare versions, reconcile totals and draft questions.

04

Disconnected conclusions

Findings are not always clearly connected to valuation, leverage, forecasts or returns.

Product example

See what Keystone actually does.

A professional diligence surface for investigating one complete claim, not a chatbot detached from the sources.

Project Atlas Customer retention investigation
Material issue - awaiting management response
Management claim Customer retention is 95%
Keystone finding Verified gross revenue retention: 84%
Potential impact Revenue forecast may be overstated.
Reason for discrepancy

Management excluded partially churned customers and used a narrower customer population than the underlying revenue file.

Recommended action

Request management's retention calculation, included customer population and treatment of acquired, renamed and partially churned accounts.

How it works

From data room to verified conclusion.

Keystone AI agent Running

Active inputs

Connect CIM, financials and data room Deal materials organized by source
Extract Management claims Revenue, customers, margins and growth
Test Evidence and calculations Conflicts traced to source records
Resolve Open diligence issues Tracked until reviewed by the team

Live workflow

Input received Keystone parses the CIM and pulls source evidence into the working session.
Source-backed finding

Management claims 18% recurring revenue growth. Keystone is locating the supporting customer file.

Connect Extract Test Investigate Drive follow-up

Live outputs

Verified metric Revenue reconciliation Source-linked evidence attached
Management question Follow-up drafted Precise request for missing support
Risk flag Retention claim needs support Awaiting investment-team review

Use cases

Built around the diligence work that changes the investment decision.

Revenue Quality

Reconcile reported revenue with customer-level data and identify unusual, nonrecurring or unsupported revenue.

Customer Retention

Calculate churn, gross retention, net retention and expansion using a consistent methodology.

Customer Concentration

Group related entities and uncover hidden exposure across subsidiaries, locations and inconsistent customer names.

EBITDA Verification

Challenge add-backs, identify recurring expenses and estimate a more defensible normalized EBITDA.

Contract Diligence

Extract pricing, renewal, termination and change-of-control risks from material agreements.

Forecast Challenge

Test management projections against historical performance, sales pipeline, churn and operating evidence.

Differentiation

Most AI tools organize the deal. Keystone investigates it.

Keystone is designed for closed-loop diligence. It helps determine what is true, what remains unsupported and what the deal team should do next.

Traditional finance AI
Keystone
Searches documents
Identifies management claims
Summarizes files
Tests claims against evidence
Extracts tables
Performs independent calculations
Answers one-time questions
Generates precise follow-up questions
Shows information
Shows potential investment impact

Traceability

Every conclusion leads back to the source.

Every claim, calculation and conclusion is linked to the underlying evidence so a deal team can inspect the exact document page, spreadsheet row, calculation or contract clause behind it.

Source-level citations Transparent calculations Document version history Conflicting evidence side by side Human approval status Complete audit trail

Human control

AI speed. Investment-team control.

Security

Designed around confidential deal information.

Enterprise security roadmap available during pilot discussions.

Encrypted data handling Deal-level permissions Role-based access controls Human approval workflows No training on customer data Configurable deletion and retention policies

Design partners

Help build the diligence agent your team would actually use.

We are working with a limited number of private equity professionals to validate Keystone's initial workflows across customer revenue analysis, management claim verification and diligence issue tracking.

Request a demo

Find the issue before it becomes the investment.

See how Keystone can help your team verify management's claims, investigate what does not add up and focus diligence on the risks that matter.