Private Equity Dashboard
See company status, reporting completeness, major changes, open risks, and value-creation actions.
Source and freshness context visible
AI For Financial Services
Private Equity Due Diligence Powered By Governed AI
Review more deal evidence without losing the thread. Mimasa AI connects approved data-room documents, financial files, contracts, reports, and internal knowledge in one controlled workflow.
Use AI due diligence to extract facts, compare claims, trace risks, prepare review packs, and monitor portfolio companies. Your investment team controls every conclusion and decision.
Source-linked findings · Human review · Controlled access · Complete workflow history
Source Document
Management report · approved version
Extracted Fact
Reported figure linked to its source passage and period.
Cited Finding
A variance needs supporting evidence before reviewer acceptance.
Open QuestionEvidence requested
OwnerDeal team reviewer
ApprovalHuman review required
Connected Review
Move From Data Room To Investment Review
Deal teams work across teasers, financial statements, contracts, reports, management responses, and operating data. Important facts can sit hundreds of pages apart.
01
Ingest Approved Material
Connect permitted files, folders, tables, and systems.
02
Extract Key Facts
Capture financial, commercial, contractual, and operating information.
03
Test Consistency
Compare claims across documents, periods, entities, and data sources.
04
Investigate Exceptions
Assign questions, owners, evidence requests, and review dates.
05
Prepare Review Outputs
Draft source-linked summaries, risk registers, and committee material.
06
Monitor After Investment
Track approved KPIs, risks, commitments, and value-creation actions.
This workflow supports professional judgement. It does not replace it.
Definition
What Is Private Equity Due Diligence?
Private equity due diligence is the structured review of a target before an investment decision.
Teams assess financial performance, market position, operations, contracts, risks, technology, and management information.
Mimasa organises evidence and workflow. Qualified investment professionals and specialist advisers remain responsible for conclusions.
Diligence Lenses
Four Diligence Lenses, One Evidence Trail
| Diligence Lens | Evidence | AI-Assisted Work | Human Decision |
|---|---|---|---|
| Financial | Statements, accounts, revenue files, working-capital data, forecasts, and reconciliations | Extract metrics, compare periods, flag gaps, and prepare variance questions | Validate adjustments, earnings quality, debt, working capital, and valuation inputs |
| Commercial | Market reports, customer data, pricing files, pipeline records, and management claims | Compare evidence, segment results, and surface conflicting claims | Judge market quality, growth assumptions, competition, and commercial risk |
| Operational | Process data, KPI packs, supplier information, staffing records, and operating reports | Structure KPIs, identify exceptions, and prepare comparisons | Assess operating resilience, capability, and improvement priorities |
| Legal And Compliance Support | Contracts, policies, registers, licences, and adviser outputs | Extract clauses, dates, obligations, and missing evidence | Form legal opinions, accept risks, and approve transaction terms |
Financial Evidence
Financial Due Diligence With Clear Source Context
Financial due diligence often reconciles narrative claims with revenue quality, margins, customer concentration, cash conversion, working capital, debt, and forecasts.
Mimasa can extract approved figures, align labels, compare claims, identify gaps, create cited questions, and route conclusions to authorised reviewers.
It does not issue quality-of-earnings conclusions, audit opinions, or valuations.
- 1Reported Figure
- 2Supporting Schedule
- 3Identified Exception
- 4Reviewer Note
- 5Approved Conclusion
M&A Review
Support M&A Due Diligence Without Replacing The Deal Team
M&A due diligence brings several workstreams together under tight deadlines. Mimasa can classify new material, update source-linked findings, notify owners, and preserve review history.
For AI for M&A due diligence, the goal is not an automatic yes-or-no answer. It is faster evidence access, clearer open issues, and a traceable route to human judgement.
Evidence Map
See How A Claim Becomes A Reviewed Finding
Keep source facts, AI analysis, reviewer comments, assumptions, and approved conclusions visibly distinct.
AI-generated text stays a draft until an authorised reviewer accepts it.
01
Management Claim
Record the claim and where it appears.
02
Supporting Evidence
Link workbook cells, document passages, contracts, reports, or system records.
03
AI-Assisted Comparison
Show matches, differences, missing periods, changed definitions, and unresolved questions.
04
Reviewer Finding
An authorised person accepts, edits, rejects, or escalates the draft finding.
05
Decision Record
Preserve the approved conclusion, owner, timestamp, and referenced evidence.
Controlled Automation
Automate The Work Around Due Diligence
Due diligence automation removes repetitive coordination, not accountability. Automated due diligence remains a controlled workflow.
Document Intake And Classification
Detect new authorised files, classify them by workstream, extract metadata, and route uncertain items for review.
Requirement And Gap Tracking
Compare received material with a configured request list. Show missing periods, incomplete schedules, and overdue answers.
Cross-Document Analysis
Find related facts across reports, spreadsheets, contracts, and responses. Return exact sources for verification.
Question Management
Draft questions from identified gaps. Assign owners and connect each answer to its original issue.
Findings And Report Preparation
Prepare structured findings, executive summaries, issue logs, and review packs using approved templates.
Approval And Escalation
Route high-impact findings, unsupported statements, and unresolved conflicts to named reviewers.
Category Boundary
AI Due Diligence Software Versus A Configurable AI Layer
Buyers may compare AI due diligence software and due diligence automation software. Mimasa supports evidence and workflow without replacing specialist systems or advisers.
| Capability | Specialist System Or Adviser | Mimasa AI Role |
|---|---|---|
| Secure Document Exchange | A virtual data room manages document hosting and deal access | Uses authorised material made available through approved connections |
| Professional Assessment | Investment, legal, finance, tax, technology, and commercial experts form conclusions | Organises evidence and prepares source-linked analysis for review |
| Financial Model And Valuation | Approved models and professionals calculate transaction values | Extracts inputs, compares assumptions, and coordinates review tasks |
| Deal Records | A CRM or deal-management platform maintains the official pipeline | Sends approved findings, tasks, or status updates through permitted workflows |
| Knowledge And Workflow | Enterprise teams need cross-source search, analysis, drafting, and approvals | Provides a configurable intelligence and agentic workflow layer |
Operational Diligence
Operational Due Diligence That Connects Data And Process
Operational due diligence examines capacity, sourcing, workforce, systems, controls, service levels, and operating KPIs.
Mimasa can compare approved data across sites, periods, products, business units, or suppliers. The operating partner decides what the evidence means.
Human-Owned Risk
Due Diligence Risk Assessment
A due diligence risk assessment should show evidence, uncertainty, impact, and ownership. One unexplained AI score is not enough.
- Finding and workstream
- Supporting and conflicting evidence
- Source links and versions
- Reviewer-selected impact
- Open questions
- Mitigation or follow-up
- Owner and due date
- Approval history
Post-Investment Continuity
From Investment Thesis To Portfolio Monitoring
Carry approved assumptions, risks, commitments, and KPIs from diligence into a controlled monitoring workflow.
01
Preserve The Approved Baseline
Capture the final investment thesis, assumptions, accepted risks, conditions, and operating priorities.
02
Collect Portfolio-Company Data
Connect approved financial and operating information. Validate fields, periods, units, and definitions.
03
Compare Actuals With The Baseline
Track plan versus actual, trends, thresholds, and agreed actions.
04
Investigate Exceptions
Prepare source-linked explanations, questions, tasks, and escalation paths.
05
Report And Act
Create approved portfolio-review packs and track value-creation actions.
This is private equity portfolio monitoring with a traceable connection to the original deal case.
Portfolio Analytics
Portfolio Analytics Built Around Approved Data
Private equity portfolio analytics connects performance, operating, risk, and action data across portfolio companies.
Private equity data analytics can compare approved KPIs, plans, forecasts, actuals, margins, growth, cash, working capital, and reporting gaps.
The firm decides definitions, materiality rules, and actions.
Private Equity KPI Dashboard
Compare approved financial and operating measures across periods, plans, companies, and business units.
Status labels support colour cues
Lifecycle Intelligence
AI For Private Equity Across The Deal Lifecycle
AI for private equity can connect evidence, workflows, analysis, and monitoring from initial review through portfolio operations.
This practical use of AI in private equity augments investment and operating teams. Private equity AI does not make investment decisions.
Screen authorised deal material
Extract facts from documents and tables
Prepare management questions
Compare targets consistently
Draft source-linked review material
Track findings and approvals
Collect portfolio information
Monitor KPIs and risks
Signal To Workflow
Private Equity Analytics Software With Workflow Built In
Traditional private equity analytics software may focus on dashboards. Mimasa connects analysis with the work that follows.
- 01Verify required data
- 02Retrieve related reports
- 03Prepare a cited exception summary
- 04Notify the responsible person
- 05Create a review task
- 06Request approval
- 07Record the outcome
Governed Agents
Private Equity Automation With AI Agents
Private equity automation coordinates repeatable tasks across documents, data, people, and approved systems.
Agents operate within role access, tool limits, and approval rules. They do not approve investments or accept risk.
Explore The Mimasa Agent Builder- Watch an approved location for new material
- Extract defined information
- Check completeness and consistency
- Retrieve relevant internal knowledge
- Draft a finding or report section
- Assign tasks and request review
- Stop when evidence is missing or conflicting
- Record each permitted action
Governance Rail
Govern Confidential Deal And Portfolio Data
Private-equity work contains confidential company, transaction, employee, customer, and financial information.
Role-based access control
Approved source and dataset boundaries
Agent tool and action limits
Source-linked answers and findings
Human approval checkpoints
Document and data version context
Workflow and approval audit trails
Governed datasets and reusable snapshots
Cloud, private-cloud, or on-premises deployment patterns
Mimasa provides configurable controls. It does not certify compliance or remove governance duties.
Controlled Rollout
Start With One Diligence Workstream
01
Choose A Repeatable Scope
Start with one document set, diligence lens, or portfolio review.
02
Define Authorised Sources
Identify which files, systems, and datasets the workflow may use.
03
Set The Output
Choose a fact table, question log, findings register, review pack, or monitoring view.
04
Mark Human Decisions
State who approves conclusions, classifications, and external outputs.
05
Build Exception Paths
Plan for missing files, conflicting values, changed definitions, and access limits.
06
Test Representative Cases
Include clean, incomplete, inconsistent, and sensitive examples.
07
Measure The Workflow
Review evidence coverage, open-question age, approval time, exception rate, and adoption.
Set baselines in your environment. Do not assume generic time, cost, or investment-performance gains.
Connected Context
Work Around Authorised Systems
Mimasa is a governed intelligence and workflow layer. It is not a fund, adviser, broker, valuation provider, auditor, law firm, data room, CRM, or books-and-records platform.
Related Workflow
Connect Diligence With Investment Research
Investment Research And Portfolio Intelligence
Search approved sources, analyse investments, monitor portfolio events, and prepare evidence-linked review briefs.
View All Use Cases →Frequently Asked Questions
Clear answers about private equity due diligence, AI-assisted review, portfolio monitoring, governance, and human control.
Get Started
Turn Deal Evidence Into Controlled Action
Connect approved documents, data, findings, reviews, and portfolio monitoring in one governed AI workflow.