15 min read
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How to choose DDQ software for outbound LP questionnaires and inbound target reviews, with the six capabilities to test and a workflow that keeps every answer sourced and approved.
Casimir Rajnerowicz
Content Creator
V7 Go
A smarter way to manage due diligence and underwriting
Question 4.7 of the LP's questionnaire asks for net IRR by fund, as of the latest quarter, with the methodology. Last month the investor relations team answered the same question for another LP, using numbers that have since been restated. Somewhere in the shared drive are three versions of the answer, and only one of them is right.
Due diligence questionnaire software exists to make sure the right one goes out, with a source behind it and a named person who approved it. For a private equity firm in market, that job repeats dozens of times per fundraise. For an M&A or buyout deal team, the same software category has a second job that runs the other way: reading a target’s completed questionnaire and checking what it says against the rest of the data room.
Both jobs are called DDQ automation, and they need different capabilities. Answering a questionnaire is retrieval from your own approved material. Reviewing one is analysis of someone else’s answers. Buying for the wrong direction is the most common reason a DDQ software purchase disappoints, so the comparison below starts with direction and only then moves to features.
The pressure on both is rising. Fundraising cycles remain long, investors keep sending custom questionnaires on top of the industry templates, and the ILPA standard has grown to cover co-investments, GP-led secondaries, credit facilities and data security.
Two directions of due diligence questionnaire software
Outbound DDQ work means answering the questionnaires investors send you. Inbound DDQ work means reviewing the questionnaires a target, a fund manager or a service provider sends back. The documents look alike, which is why buyers confuse them, but the work, the owner and the output are different.
Outbound: answering a DDQ | Inbound: reviewing a DDQ | |
|---|---|---|
Typical sender and receiver | LP or consultant sends to the GP | Buyer or LP sends to a target or manager, who returns answers |
Who owns the work | Investor relations, compliance, CFO | Deal team, LP diligence team, operational due diligence |
Main inputs | PPM, Form ADV, LPA, prior DDQs, policies, track record | Completed DDQ, data room, financials, contracts |
Core task | Find the approved, current answer and adapt it | Extract facts, find gaps and contradictions |
What failure looks like | A stale or inconsistent figure sent to an LP | A contradiction nobody spotted before IC |
Where the output goes | LP portal or the investor’s own format | Issues list, deal record, IC memo |
If you need a primer on the questionnaire itself, its sections and how the ILPA template is used, our guide to the due diligence questionnaire covers it. The rest of this page is about the software.
The outbound load on a fundraise
Custom questionnaires are the norm. DiligenceVault’s manager survey found that 97% of managers receive at least one custom DDQ from investors, and that 40% of managers with $10 billion to $50 billion in AUM handle between 100 and 500 RFP and DDQ requests a year.
Each one takes time to get right. In an SS&C Intralinks survey of US investor relations and fundraising professionals published in July 2026, more than 40% said a single DDQ typically takes four days or longer, and 14% said it takes more than a week. Drafting the first responses and securing internal approvals were each named as bottlenecks by 43%.
The calendar makes this worse. Preqin’s Q2 2026 private equity update notes that more than half of funds are taking between 19 and 30 months to close. Over that period, figures change, people leave and the same question gets answered from different quarters.
Here is the arithmetic for a hypothetical mid-market GP in market. Forty questionnaires at an average of 250 questions is 10,000 answers. If 75% can be drawn from previously approved answers with a citation to the current source, 2,500 still need fresh drafting or a subject-matter expert. A 10% review sample of the reused answers adds 750, so the team reviews or writes 3,250 answers instead of 10,000, about a third of the load.
Step | Answers | Who handles it |
|---|---|---|
Questions received (40 DDQs x 250) | 10,000 | Workflow maps each to the firm’s question bank |
Matched to an approved, current answer | 7,500 | Drafted with citation, ready for sign-off |
New or changed questions | 2,500 | IR drafts, SMEs answer, compliance approves |
Sample review of reused answers (10%) | 750 | Compliance |
Answers a person writes or reviews | 3,250 | About 32% of the total |
Mapping custom questions to the ILPA base
Reuse depends on recognising the same question under different wording. ILPA released DDQ 2.0 in November 2021, adding sections on co-investments, GP-led secondaries, credit facilities and data security, and many managers keep a completed ILPA DDQ as their base. Investors then send their own versions, which reorder, split and rephrase the same questions.
How the question arrives | Question family it maps to | What changes in the answer |
|---|---|---|
Describe the firm’s valuation policy and who approves valuations. | Valuation policy and governance | Nothing, if the policy is unchanged |
Has the valuation methodology changed since the prior fund? | Valuation policy and governance | Add the comparison with the prior fund |
Who sits on the valuation committee? Attach the charter. | Valuation committee | Current members and the charter as an attachment |
How often are portfolio valuations reviewed by a third party? | Valuation oversight | Frequency and the firm used, from the latest year |
Mapping by question family, rather than by exact text, is what lets a firm answer a new investor’s 300 questions mostly from material compliance has already approved. It also exposes genuinely new questions early, so the owner has time to answer them before the deadline.
An outbound answer is only defensible when the reviewer can open the PPM page it was drawn from.
The inbound problem on a deal
Inbound review is where questionnaires hide risk. A target’s completed DDQ arrives as a mix of Word responses, Excel schedules and PDF attachments, often in the last week before IC. The answers are technically complete, and the problems sit between them: a litigation answer that contradicts a provision in the financial statements, a customer concentration figure that differs from the CIM, or an attachment that was promised and never uploaded.
DDQ question (example) | Target’s answer | Cross-check | Finding |
|---|---|---|---|
Any material litigation in the last 5 years? | None | Notes to 2025 accounts mention a provision for a claim | Contradiction, ask the seller |
Top 10 customers as % of revenue | 38% | CIM states 46% | Figure mismatch, confirm the period |
Change-of-control clauses in key contracts | See attached schedule | Schedule not in the data room | Missing attachment |
Data protection incidents | No reportable incidents | Board minutes reference a regulator letter | Follow up with counsel |
McKinsey’s research on gen AI in M&A shows the largest time savings in exactly these document-heavy diligence stages. The value comes from cross-checking every answer, which a deal team under deadline rarely has time to do by hand.
Diligence is one of the slowest stages of a deal, and the target’s questionnaire is one of its densest documents.
The same inbound pattern applies to LP diligence on a manager and to operational due diligence on a service provider. Our guide to LP due diligence on GPs covers how allocators score the answers they receive.
Comparing due diligence questionnaire software by category
The market splits into four categories, and each is strong at one job and stops at the edge of another. Describe your own workflow first, then shortlist only the category that matches it.
Category | Built for | Where it is strongest | Where it stops |
|---|---|---|---|
Response management platforms | Enterprise RFP, security questionnaire and DDQ volume | Content libraries, assignment, collaboration across large teams | Library upkeep is manual, and inbound review is out of scope |
Private-markets diligence platforms | LP and GP exchange of DDQs and fund data | Industry templates such as ILPA, portals, structured fund data | Usually tied to the exchange itself, with less analysis of free-text answers |
Answer engines over a firm’s documents | Drafting answers from indexed documents | Fast first drafts with citations | Approval history and inbound cross-checks vary widely |
Workflow platforms for repeatable document work, such as V7 Go | Defined steps over the firm’s knowledge, in both directions | Citations, review gates, cross-document checks, outputs to other systems | Needs the process designed with the team before rollout |
Private Markets
Turn complex deal documents into better investment decisions.
Two questions decide most shortlists. First, which direction dominates your volume? Second, who will own the approved answers a year from now? A content library without an owner decays quietly until someone sends a stale AUM figure to an LP, so a platform that draws answers from current source documents changes the maintenance burden more than any feature list.
Our broader guide to due diligence software covers data rooms and diligence workspaces, which sit alongside DDQ software rather than replacing it.
Running DDQ work as a repeatable process with V7 Go
V7 Go is the operating system for repeatable work, and it runs both directions of DDQ work on the firm’s own knowledge. Your systems of record stay authoritative. V7 Go reads the questionnaire and the source documents, applies the firm’s rules and sends reviewed answers or findings where they need to go.
Outbound: answering an LP questionnaire
The questionnaire arrives in Excel, Word, PDF or portal export, and the workflow maps each question to the firm’s question bank.
For each question it drafts an answer from the current PPM, Form ADV, policies and approved prior responses, citing the source page.
Questions with no approved answer, or whose source has changed since approval, go to the right owner in IR, compliance or finance.
Compliance approves, approved answers are locked with a timestamp, and the response is exported in the investor’s format.
Every approved answer becomes part of the firm’s knowledge for the next questionnaire, so the question bank improves with each fundraise. The DDQ completion use case and the DDQ response agent show the outbound workflow.
Inbound: reviewing a target’s responses
The completed questionnaire and its attachments arrive in the data room or by email, and the run starts.
The workflow extracts the answers that drive the decision, such as ownership, litigation, customer concentration and regulatory status.
It compares each answer with the CIM, accounts and contracts, and lists contradictions, gaps and missing attachments with both sources cited.
The deal lead reviews the issues list, sends questions back to the seller and carries confirmed findings into the IC memo.
Both DDQ directions follow the same steps, with the schema and review rules set for each workflow.
Findings flow onward instead of sitting in a separate tool. Confirmed issues can populate the deal record and feed investment memo generation, and the firm’s wider finance and private markets workflows read the same knowledge. The walkthrough below shows how the finance workflows fit together.
How V7 Go runs finance workflows, from DDQ completion to CIM extraction, with every answer traceable to its source.
Volumes and timing differ by firm, so measure against your own baseline: turnaround per questionnaire, hours of senior review, the share of answers reused from approved material and the number of corrections after submission.
Each highlighted figure links back to the passage it came from, which is what lets compliance approve an answer quickly.
Building an approved answer bank that stays current
Outbound DDQ software is only as good as the answers it draws on, and most firms underestimate the governance this takes. An answer bank needs the same discipline as a policy manual: an owner for every answer, a source for every fact and a date after which it must be checked again.
Treat each approved answer as a record with fields, not a paragraph in a document. The fields below are the minimum that lets a reviewer trust a reused answer without rereading its source.
Field | Example | Why it matters |
|---|---|---|
Question family | Track record, net IRR by fund | Maps differently worded questions to one approved answer |
Approved text | Net IRR as of 30 June 2026, by fund, with methodology | The wording compliance has signed off |
Source document and page | Q2 2026 quarterly report, page 4 | Lets a reviewer verify the figure in one click |
Data as-of date | 30 June 2026 | Stops an old quarter being sent as current |
Owner | Head of investor relations | Someone is accountable for updating it |
Approver and approval date | CCO, 14 August 2026 | The audit trail LPs and regulators ask for |
Review trigger | Next quarterly report or any restatement | Forces a refresh when the source changes |
Restrictions | Not for marketing use, LP-only | Keeps sensitive answers in the right channel |
Set review triggers by source, not by calendar. Performance answers change every quarter, team answers change when someone joins or leaves, and policy answers change when the compliance manual is updated. A workflow that watches the source documents can flag every dependent answer the day a new quarterly report lands, which a calendar reminder cannot do.
Expect the first consolidation to take longer than the software rollout. Most firms find several conflicting versions of their most common answers across past submissions, and choosing the approved one is a compliance decision, not a technology one.
An inbound DDQ review checklist by section
Inbound review works best when every section of the questionnaire has a named document to check it against. The checklist below covers a buy-side review of a target’s DDQ. LP diligence teams reviewing a manager can use the same structure with fund documents in place of company ones.
DDQ section | Check the answer against | Typical red flag |
|---|---|---|
Corporate and ownership | Cap table, shareholder agreements, registry filings | Undisclosed shareholders or options |
Financial | Audited accounts, management accounts, QoE report | Revenue or EBITDA that differs from the CIM |
Customers and contracts | Top customer contracts, revenue by customer | Concentration understated, change-of-control terms |
Legal and litigation | Notes to the accounts, board minutes, legal letters | A provision or claim the answer omits |
Employees | Org chart, employment contracts, incentive plans | Key-person dependence, unusual severance terms |
Regulatory and compliance | Licences, regulator correspondence, policies | Open regulatory matters described as closed |
IT and data security | Security policies, incident logs, certifications | Incidents not reported, expired certifications |
ESG | Sustainability reports, policies, supplier data | Claims without supporting data |
Two rules keep the review honest. Every finding cites both sources, the answer and the document it conflicts with, so the seller can respond precisely. And unanswered or deferred questions count as findings, because “to be provided” in a DDQ often means the information does not exist in the form the buyer expects.
Rolling out DDQ software in four steps
A rollout succeeds when the first live questionnaire produces a better answer set than the last manual one. Plan it in four steps and measure each against your own baseline.
Step | What happens | Done when |
|---|---|---|
1. Baseline | Time and count the last two questionnaires: answers written fresh, approvals, corrections after submission | You have a number to beat |
2. Consolidate | Pick the approved version of each common answer, link it to its source, assign owners | The top 200 answers have owners and sources |
3. Pilot | Run one outbound and, if relevant, one inbound questionnaire end to end | Turnaround and corrections beat the baseline |
4. Extend | Add review triggers, more question families and the next team | Answers refresh when sources change |
Keep the pilot small and real. A live LP questionnaire with a deadline teaches more about approval routing and source quality in a week than a quarter of testing on samples.
Which teams buy DDQ software, and for what
The same category serves four different buyers, and each weighs the capabilities differently. Knowing which buyer you are keeps the demo focused on the tests that matter to you.
Buyer | Main direction | What they need most |
|---|---|---|
GP investor relations and compliance | Outbound | Approved answers, approval history, export in each investor’s format |
LP and consultant diligence teams | Inbound | Consistent extraction across managers, comparison with fund documents |
Buy-side M&A and deal teams | Inbound | Cross-checks against the data room, issues list, link to the IC memo |
Operational due diligence and vendor risk | Both | Evidence requests, policy checks, repeat reviews each year |
Firms that sit in more than one row, such as a GP that also runs buy-side diligence, get the most from a platform that handles both directions on the same knowledge. The answers investor relations approves about the firm’s own policies are also the reference point when the deal team asks a target the same questions.
Six capabilities to test in a DDQ software demo
Run the demo on one of your own questionnaires, not the vendor’s sample. These six tests separate tools that will hold up in a compliance review from ones that only look good on screen.
Capability | What to ask the vendor | A good answer looks like |
|---|---|---|
Source attribution | Show me where this answer came from. | One click opens the exact page, cell or clause, with its date |
Approval history | Who approved this answer, and when? | Every answer carries an approver and timestamp, and approved text is locked |
Currency | What happens when AUM changes next quarter? | Answers built on the old figure are flagged for update everywhere |
Format handling | Can you take this Excel and this PDF questionnaire as sent? | No manual reformatting, and output returns in the LP’s own format |
Inbound cross-checks | Compare this target’s DDQ with its CIM and accounts. | Contradictions and missing attachments listed with both sources cited |
Security and data use | Where is our data processed, and can any model train on it? | Documented residency and retention, and a contractual no-training commitment |
Accuracy is the concern buyers raise most. In the Intralinks survey, 62% of respondents named the risk of inaccurate or fabricated responses as their most significant concern about AI in the DDQ process. Source attribution and approval history are the two capabilities that answer that concern directly, because they let a reviewer verify an answer instead of trusting it.
Fund metrics carry their source document and extraction time, the provenance an LP’s operational due diligence team expects to see.
Choose DDQ software by direction first and features second. If most of your questionnaires are outbound, buy for approved-answer management, source attribution and approval history. If your deal or LP diligence team spends its weeks reading other people's answers, buy for cross-document checks and an issues list that feeds the IC memo.
Before any demo, pull the last questionnaire your team submitted and count the answers that were drafted from scratch. That number, and how long the approvals took, is the baseline any tool has to beat.
What is due diligence questionnaire software?
Due diligence questionnaire software manages the questions and answers that investors, acquirers and allocators exchange before committing capital. On the outbound side it helps a fund manager or company answer questionnaires it receives, by drafting responses from approved material, routing new questions to the right owner and recording who approved each answer. On the inbound side it helps the party that sent the questionnaire review the answers that come back, by extracting the key facts, comparing them with other documents and listing gaps or contradictions. Some products cover only one side. Response management platforms and private-markets diligence portals focus mainly on outbound work, while workflow platforms can handle both directions. The common thread is evidence: every answer should be traceable to a source document and an approver, because questionnaires are reused, audited and relied on in investment decisions.
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What is the difference between outbound and inbound DDQ work?
Outbound DDQ work is answering a questionnaire someone sends you, such as an LP's DDQ to a private equity manager. The task is retrieval and consistency: finding the current, approved answer in the firm's PPM, Form ADV, policies and prior responses, adapting it to the question and getting it approved. Inbound DDQ work is reviewing a questionnaire that has been answered by someone else, such as a target company in an acquisition or a manager under LP diligence. The task is analysis: extracting the facts, checking them against the CIM, accounts, contracts and data room, and raising contradictions or missing attachments. The two need different capabilities. Outbound work depends on approved-answer management and approval history, while inbound work depends on extraction and cross-document checks. Many firms do both, often in different teams, which is why the direction should be settled before comparing tools.
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Can AI answer a DDQ without human review?
It should not, and well-designed tools do not try. AI can draft most answers in a typical LP questionnaire by matching each question to approved responses and current source documents, and it can flag the questions that have no approved answer or whose source has changed. That shifts the team's work from writing to reviewing. A person still needs to approve each answer before it goes out, because the firm is accountable for what it tells investors and some questions involve judgement, new facts or regulatory sensitivity. The practical design is to route only new, changed or low-confidence answers to subject-matter experts, to sample a fixed share of reused answers for compliance review, and to lock approved text with the approver's name and a timestamp. That keeps accuracy where it needs to be while removing most of the repetitive drafting from senior staff.
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How does the ILPA DDQ relate to DDQ software?
The ILPA Due Diligence Questionnaire is the industry template institutional investors use to assess private equity managers. ILPA released version 2.0 in November 2021 with a new structure and added sections on co-investments, GP-led secondaries, credit facilities and data security, and it adopted the PRI's responsible investment DDQ as its ESG section. Many managers maintain a completed ILPA DDQ as their base document, but most still receive custom questionnaires that reorder, rephrase or extend the ILPA questions. DDQ software helps by mapping each incoming question, whatever its wording, to the corresponding approved answer, so the ILPA base can be reused across investors without copy-and-paste errors. When reviewing a manager's ILPA DDQ as an LP, software helps in the other direction by extracting answers into a consistent structure that can be compared across managers and checked against fund documents.
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How long does it take to implement DDQ software?
It can be, provided the platform meets the standards you already apply to your data room and investor portal. DDQs contain confidential fund terms, performance data, investor information and, on the inbound side, a target's non-public financials and contracts. Before uploading anything, confirm where data is processed and stored, whether a regional deployment or data residency option is available, how long documents and run history are retained and how access is controlled across teams and projects. Ask for current certifications and read the security documentation, and get a written commitment on whether any model provider can train on your data. Check that every answer and finding keeps a link to its source and an approval record, since those are what auditors and LPs will ask for. Settle these questions once at platform level so each new questionnaire workflow does not need its own security review.
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Is it safe to use AI for due diligence questionnaires?
Go is more accurate and robust than calling a model provider directly. By breaking down complex tasks into reasoning steps with Index Knowledge, Go enables LLMs to query your data more accurately than an out of the box API call. Combining this with conditional logic, which can route high sensitivity data to a human review, Go builds robustness into your AI powered workflows.
