Operational AI for Due Diligence
AI for due diligence, from data room to IC memo
Due diligence automation that reads every file in the data room, reconciles the numbers, flags what is missing, and cites every claim back to its source.
See it on your own data
Operational AI for Due Diligence
AI for due diligence, from data room to IC memo
Due diligence automation that reads every file in the data room, reconciles the numbers, flags what is missing, and cites every claim back to its source.
See it on your own data
Operational AI for Due Diligence
AI for due diligence, from data room to IC memo
Due diligence automation that reads every file in the data room, reconciles the numbers, flags what is missing, and cites every claim back to its source.
See it on your own data
Shaping the
future
of investment diligence.
Shaping the
future
of investment diligence.
Shaping the
future
of investment diligence.
Deal teams do not need AI that merely reads documents
They need systems that execute diligence end to end
Ingesting an entire data room, building the diligence checklist, reconciling financial and operational data across sources, identifying omissions and contradictions, testing key assumptions, and producing an investment-committee-ready view with every conclusion traceable to evidence. That is the standard institutional investors should demand.
The diligence workflows firms automate first.
Data Room DD
Before
100+ Hours
with V7
less than 10 Hours
Data Room DD
Before
100+ Hours
with V7
less than 10 Hours
Data analysis cost
Before
$2.5M
with V7
$100K
Data analysis cost
Before
$2.5M
with V7
$100K
CIM > IM process
Before
5–7 Hours
with V7
15 Minutes
CIM > IM process
Before
5–7 Hours
with V7
15 Minutes
Building this in-house would've cost us $2M and 18 months. V7 had us live in six weeks.
Head of AI, Tech-Forward Insurance Brokerage
Our workflows were live in days, not months. The support is unlike anything we've seen from an enterprise vendor.
Alaris Acquisitions
Every serious fund will be running AI-powered diligence within two years. V7 is the only platform we'd trust with that.
Investment Firm Partner
We're processing hundreds of complex deal documents a week. What used to take a team now takes an afternoon.
Pinsent Masons
We replaced three separate tools — and cut our workflow costs by 40%. One platform does it all.
Real Estate Innovator
21x faster processing. 54% fewer errors. We now screen 5x more opportunities with the same team.
Star Mountain Capital ($5B alt asset firm)
We evaluated eight vendors. V7 wasn't close — it was the only one built for how private markets actually work.
AI-First Insurance Brokerage
AI that understands due diligence, built by experts.
Constance Freedman
Founder and Managing Partner
Moderne Ventures
Constance Freedman
Founder and Managing Partner
Moderne Ventures
From data room review to red-flag reports, IC memos and confirmatory diligence, V7 Go workflows turn fragmented deal files into investment-ready findings.
V7 Go is not a data room, CRM, or portfolio management system. It’s the context layer for diligence. It connects documents, spreadsheets, research, and firm knowledge so AI agents can execute a full diligence process, with every output traceable to its source.
Diligence intelligence at institutional scale.
The ROI of due diligence automation, workflow by workflow.
Five document-heavy workflows that sit around every diligence process, measured in hours saved per deal, per fund, and per reporting cycle.
Use Case
Input
Interim steps
Output
Time Savings
ROI
Data Room Diligence Review
OMs, CIMs, NDAs, contracts, models
Read full documents → Extract financials / risks → Summarize key points → Build comps
Deal summaries, red flags, side-by-side comparables
10–15 hrs / deal
$100k+ annually × 2–4× firm size
Portfolio KPI Extraction
Monthly / quarterly ops reports, lender updates, board decks
Manually locate metrics → Copy/paste into Excel → Normalize + trend
Time-series dashboards + trend alerts
5–8 hrs / month
$50k+ annually × 1.5–2× firm size
NDA Review
NDA guidelines, NDA document
Review each NDA → Compare to guideline criteria → Create issues report
Issues report for each NDA
1–3 hrs / week
$25k+ annually × 1–1.5× firm size
LPA & Fund Doc Analysis
LPAs, side letters, fund marketing docs
Read lengthy docs → Identify economic/legal terms → Cross-compare with precedent docs
Extracted terms + compliance risk flags
7–10 hrs / fund
$40k+ annually × 1.5–2× firm size
Compliance & Regulatory Checks
Deal docs, ESG/AML checklists
Manually cross-check clauses → Flag red flags → Compile into risk report
Auto-flagged risks with audit trail
6–10 hrs / fund
$75k+ annually × 1.5–3× firm size
Compliance & Regulatory Checks
Deal docs, ESG/AML checklists
Manually cross-check clauses → Flag red flags → Compile into risk report
Auto-flagged risks with audit trail
6–10 hrs / fund
$75k+ annually × 1.5–3× firm size
We used V7 Go to automate our diligence process with data extraction and automated analysis. This led to a 35% productivity increase in just the first month of use.
We used V7 Go to automate our diligence process with data extraction and automated analysis. This led to a 35% productivity increase in just the first month of use.
Document Type
20+ Page Reports
We use Collections on V7 Go to automate completion of our 20-page safety inspection reports. The system analyzes photos and supporting documentation and returns structured data for each question. It saves us hours on each report.
From first call to commercials in 11 days.
No twelve-month transformation. No “phase 1 of 4.” Our solutions team ships you a working pilot on your real diligence documents in eleven business days, then you decide whether to commercialize. This is the actual sequence we ran with our last twelve private-markets customers.
Day 1
Introductory call
30 minutes with a solutions engineer. We learn your documents, your existing systems, your bottleneck.
Day 2
POC scoping
We map a single high-value diligence workflow, like data room review, DDQ completion, or red-flag reporting, to a concrete, repeatable process.
Day 3
POC kickoff
Sample data room files flow through the workflow in your sandbox. Outputs are wired to your downstream system.
Day 5
POC check-in
Solutions team reviews outputs with your deal team. Tunes prompts, fields, and citation thresholds.
Day 10
Results review
Side-by-side: V7 outputs vs. your team’s manual diligence. Accuracy, time, and citation rate measured.
Day 11
Commercials
Production rollout plan. Pricing tied to throughput. SOC 2 Type II pack delivered for InfoSec review.
Enterprise-grade security.
Your data stays yours—always. Work with one of the few AI companies that never trains on your data.
No training on your data
Encrypted end-to-end
Audited and penetration-tested
Fine-grained access controls
Inhouse security team
Audit logs across every workflow
Enterprise-grade security.
Your data stays yours—always. Work with one of the few AI companies that never trains on your data.
No training on your data
Encrypted end-to-end
Audited and penetration-tested
Fine-grained access controls
Inhouse security team
Audit logs across every workflow
Enterprise-grade security.
Your data stays yours—always. Work with one of the few AI companies that never trains on your data.
No training on your data
Encrypted end-to-end
Audited and penetration-tested
Fine-grained access controls
Inhouse security team
Audit logs across every workflow
Have questions?
Why not just use Claude or ChatGPT for due diligence?
V7 Go and large language models serve different purposes. Claude, ChatGPT and Gemini provide the underlying reasoning; V7 Go provides the infrastructure required to apply that reasoning reliably across real investment workflows.
V7 Go can run workflows using models such as Claude, or operate as an MCP server that lets your team access V7 workflows and institutional knowledge directly from Claude, ChatGPT or another compatible assistant. It connects the model to your documents, systems, permissions, business rules and output templates—then manages multi-step execution, source verification and human review.
You are also buying more than software. V7’s solution engineers help design, build and deploy automated workflows around your firm’s processes, from CIM screening and diligence to IC memos and portfolio reporting.
Does V7 Go work with our data room and existing systems?
Yes. V7 Go is designed to work alongside your existing technology stack rather than replace every system in it. It supports integrations with private-markets platforms and data providers including Bipsync, PitchBook and DealCloud, as well as tools such as SharePoint, Salesforce and Snowflake.
Through native integrations, APIs and MCP connectors, V7 Go can retrieve information from your current systems, process it and return structured outputs to the applications where your team already works. Custom connectors can also be developed for proprietary or legacy systems.
Can V7 Go use our entire body of institutional knowledge?
Yes. V7 Go’s Knowledge Hubs bring together information from data rooms, spreadsheets, IC memos, LP letters, research, call transcripts and other internal sources. Its proprietary Index Knowledge and Context Graph technologies organize that information around entities, figures, clauses and relationships—not merely isolated text fragments.
Unlike basic RAG systems, which retrieve a handful of semantically similar passages, V7 Go builds a structured map of the available knowledge and identifies the evidence relevant to each question. This enables it to synthesize information across large, mixed-format document collections without attempting to place the entire knowledge base inside a single LLM prompt. Answers remain connected to their underlying sources for verification.
Can we trust AI findings on high-stakes diligence?
V7 Go is designed to make AI output reviewable rather than asking deal teams to accept a black-box answer. Extracted figures, clauses and conclusions can be linked to the relevant page and location in the original source material, allowing analysts and investment committees to verify the evidence quickly.
How does V7 Go protect confidential deal data?
V7 Go is built for sensitive institutional information. Its published security controls include SOC 2 Type II certification, end-to-end encryption, fine-grained access controls and workflow audit logs. Customer data is not used to train its models and that inference operates with zero-retention processing.
Permissions can be configured so users and agents only access the deals, portfolio companies or knowledge sources relevant to their roles. This allows firms to automate workflows involving confidential CIMs, financials and LP information without making that content broadly available across the organization.
Precision AI for due diligence workflows
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