HOLD.co

Technology · HOLD.co portfolio

VDR.ai — the AI virtual data room built for modern deal teams.

VDR.ai combines a secure virtual data room with agentic due diligence, cross-document reconciliation, clean team workflows, and private AI controls — so buyers, sellers, sponsors, lenders, and advisors move from document chaos to decision-ready outputs.

A HOLD.co company

Built inside the portfolio it was built for.

VDR.ai is a wholly owned technology subsidiary of HOLD.co, sitting alongside DEV.co, LLM.co, Automatic.co, SEC.co, and Search.co in our technology segment — and directly adjacent to the finance segment that gave rise to it.

The product started as internal infrastructure. HOLD.co and its advisory brands — InvestmentBank.com, MergersAndAcquisitions.net, and PrivateEquityInvestor.com — run acquisitions, diligence, and capital raises continuously, and the tooling available for that work stopped at document storage. VDR.ai was built to close the gap between a file repository and an actual diligence workspace, then hardened into a commercial platform.

That origin is the durable advantage: every workflow in VDR.ai was specified by people closing transactions, and it is exercised on live deals inside the portfolio before it ships to clients.

The problem

A data room tells you a file was opened. It does not tell you what the file means.

Diligence is where transactions slow down, cost money, and go wrong. The category built for it never moved past secure storage.

Storage is not diligence

Traditional data rooms report who opened which file. They do not structure the review, surface what is missing, or organize the outputs a deal team actually has to produce.

Manual review does not scale

A single mid-market transaction can carry thousands of documents. Human-only review is slow, expensive, and inconsistent across reviewers and workstreams.

Deal files disagree with each other

The model, the contracts, the schedules, the statements, and the tax returns rarely reconcile. The mismatches are where the value — and the risk — hides.

Sensitive data needs controlled review

Competitively sensitive and regulated information has to be reviewable without being fully disclosed, with an auditable record of who saw what.

The product

Six modules on one permissioned spine.

Everything shares a single authorization model, a single AI orchestrator with pre-run cost estimates and approval gates, and a single citation layer — so an output can always be traced back to the source page it came from.

01

Virtual data room

Upload, organize, permission, watermark, track, and share confidential transaction documents. Nested folders with inherited policies, malware scanning that fails closed, Office-to-PDF preview, approval-gated downloads, external guest access, and per-document view-duration tracking.

02

AI diligence agents

Task-specific agents read across the entire file for legal, financial, tax, HR, IP, debt, real estate, insurance, and regulatory review — each finding tied back to a citation span in the underlying source document.

03

Cross-document reconciliation

Automated comparison across models, contracts, statements, schedules, tax returns, customer lists, and disclosures, flagging the mismatches a reviewer would otherwise find in week three.

04

Clean team clean room

Restrict competitively sensitive information while permitting AI-mediated, aggregate-only insight — with attestation, approval queues before outputs are shared, and an exportable compliance record.

05

Private AI controls

Configure AI review against zero-retention, private cloud, sovereign residency, or on-premise requirements, with provider and model allowlists that fail closed and a per-workspace AI policy.

06

Deal outputs

Quality-of-earnings workbooks, valuations, CIMs and teasers, IC memos, lender packages, risk registers, diligence summaries, Q&A responses, and closing checklists — exportable to HTML, XLSX, DOCX, and PDF.

AI diligence agents

Task-specific agents, not a chat box over a folder.

Each agent is scoped to one diligence workstream, runs as a durable map-reduce job across the full document set, and returns findings with span-level citations into the source file. A representative slice of the catalog:

Covenant summary

Loan terms, restricted payments, consent requirements, defaults, guarantees, change-of-control provisions.

Change of control

Assignment restrictions, consent triggers, termination rights, acceleration clauses, counterparty approvals.

IP liability

IP ownership, contractor assignment language, open-source exposure, licensing restrictions, infringement risk.

Revenue quality

Customer contracts against revenue schedules, AR aging, churn, concentration, and recurring-revenue claims.

Lease abstraction

Rent, renewal options, assignment restrictions, CAM obligations, landlord consent requirements.

HR & benefits

Employee census, compensation, benefits, contractor classification, offer letters, severance obligations.

Litigation

Pending claims, demand letters, settlement agreements, threatened disputes, contingent liabilities.

Tax

Tax return data, nexus issues, payroll and sales tax exposure, unusual adjustments.

Insurance

Coverage, exclusions, claims history, policy limits, and gaps.

Cyber & privacy

Privacy policies, DPAs, SOC reports, cyber insurance, breach history, regulatory exposure.

Deployment

Your data, on your terms.

Regulated buyers, sovereign funds, and antitrust-sensitive transactions each have different constraints. VDR.ai is deployable against all of them.

Cloud

Standard secure hosted environment for modern deal teams.

Private cloud

Dedicated tenant, isolated storage, and a private processing environment.

Sovereign AI

Data residency and regional processing controls for regulated or jurisdiction-sensitive transactions.

On-premise

Deployed inside the client's own infrastructure for the most sensitive enterprise use cases.

Security & governance

Access control is the architecture, not a setting.

Confidential transaction data sets the floor for how the platform is built. Permissions are enforced at every layer — including before the model ever sees a document.

Row-level tenant isolation on every record
Central permission check on every route, API, and AI retrieval
Permission-filtered retrieval — no global index
Malware scanning before any AI touches a file
Zero-data-retention AI posture with attestation
Watermarked viewing and approval-gated downloads
Filterable audit log with CSV export
Claim classification and a publish gate on every output
Two-factor authentication and session revocation
Per-workspace AI spend caps and approval thresholds

Who it serves

Both sides of the table.

Sell-side preparation, buy-side diligence, lender review, and advisory workstreams all run in the same room with different permissions.

Private equity firms
Independent sponsors
Investment bankers
M&A advisors
Real estate investors
Lenders
Law firms
Accounting firms
Corporate development
Family offices
Business owners
Strategic buyers

Our thesis

Diligence is the last major transaction workflow still done by hand. The firms that industrialize it will underwrite more deals, more accurately, with smaller teams — and VDR.ai is the operating layer that gets them there.

See VDR.ai on a live deal file.

Walk through the data room, run a diligence agent against your own documents, and review the outputs — or talk to the HOLD.co team about the platform.

Interested in the platform or the portfolio?

Whether you want to run a transaction on VDR.ai or you're an owner, operator, or investor exploring a deal with HOLD.co, start a confidential conversation.