The deal team frames it.
The platform executes it.
DiligenceIQ does not remove human responsibility from the deal process. It separates the work that requires professional judgement from the work that can be executed, repeated and scaled through AI — then keeps a traceable line between the two.
Humans lead the diligence. AI executes the workflow.
The deal team.
Scope, interpretation, challenge and the final recommendation.
- 01Define the investment thesis.
- 02Set the diligence scope.
- 03Identify key deal questions.
- 04Select and prioritise workstreams.
- 05Add transaction and sector context.
- 06Challenge findings and assumptions.
- 07Review material evidence.
- 08Approve outputs.
- 09Own the final recommendation.
DiligenceIQ.
Execution, repetition and scale, under human direction.
- 01Ingest and organise deal documents.
- 02Connect information across sources.
- 03Analyse defined diligence questions.
- 04Run specialist workstreams in parallel.
- 05Identify inconsistencies and information gaps.
- 06Surface potential red flags.
- 07Produce source-linked findings.
- 08Draft management questions.
- 09Generate IC-ready draft outputs for human review.
- 10Re-run analysis when new information arrives.
The boundary is a design principle, not a disclaimer. Nothing crosses from the execution layer into an investment recommendation without a named person reviewing the evidence behind it.
Five stages, run as a loop rather than a handoff.
New documents, questions and management responses can be added at any point and the relevant analysis re-run. The diligence view stays current as the evidence base grows.
Frame
Define the transaction context, investment thesis, diligence scope and key deal questions.
Ingest
Analyse data room documents, management information, external research and other approved sources.
Investigate
Run specialist diligence workstreams in parallel and test the available evidence against the deal questions.
Challenge
Identify inconsistencies, evidence gaps, counterarguments, red flags and areas requiring further management input.
Decide
Produce source-backed findings, management questions, risk summaries and IC-ready draft outputs for human review.
One deal memory — not a pile of files.
Every stage reasons over one connected structure rather than over loose documents. That is why a figure on page 400 of one file can be tested against a claim in another, and why a contradiction becomes an open question instead of going unnoticed.
What goes in
- Data room
- Management information
- External research
- Deal questions
One structure
- Company
- Customers
- Products
- KPIs
- Contracts
- Competitors
- Risks
Everything reasons over this, not over loose files.
What comes out
- Questions — deal and management questions, drafted
- Findings — cross-checked, contradictions flagged
- Evidence & gaps — linked to source, or recorded as a gap
Each transaction can strengthen the next.
Where a firm authorises it, deal memory extends beyond a single transaction — turning the firm's methodology, prior diligence, IC questions, decisions and post-deal outcomes into reusable institutional context. The point is not storing old documents; it is that institutional knowledge compounds across transactions instead of leaving with the analyst who ran the last one.
Your methodology
Diligence playbooks, standard question sets and output templates encoded once and applied consistently.
Prior diligence
Evidence and findings from earlier transactions available as context — sector patterns, comparable assets, recurring risks.
IC questions
The questions your committee actually asks, applied earlier — so papers anticipate challenge rather than absorb it in the room.
Investment decisions
What was approved, what was passed on, and the reasoning recorded at the time.
Post-deal outcomes
What the asset actually did after completion, tested against what diligence predicted.
Knowledge that compounds
A diligence capability that sharpens with every transaction rather than starting from zero.
Nothing crosses between transactions without explicit authorisation from the firm, and nothing crosses between clients under any configuration. Cross-deal context is configured per firm, governed by the same access controls as the underlying evidence, and can be switched off entirely.
What the Investigate stage looks like on a live deal.
Workstreams in progress
Interface shown with illustrative data. Workstreams are activated per transaction — this is one configuration, not a fixed set.
Challenge starts with knowing what you do not have.
Every requirement in the agreed scope is mapped against the evidence base. What sits in the data room, what is only partially supported, what can be sourced externally and what needs primary research — visible while there is still time to act on it.
Evidence coverage & gap analysis
It turns “we have not looked at that yet” into a specific, assignable action — a management question, a research task, or a confirmation that the evidence is already in the room.
Gaps become a management question list and a research plan. The deal team decides what is material enough to chase — the platform does not close a gap by inference.
Interface shown with illustrative data. Coverage is a view of the evidence base, not an assessment of the transaction.
It sits alongside your existing process
DiligenceIQ works with your current data room and diligence workflow. It ingests the documents you already have and produces structured outputs that feed the process you already run — no migration required.
Your methodology stays yours
Deal questions, workstream configuration and output templates align to your playbook and IC format. The platform is a configurable execution layer, not a methodology imposed on the team.
Put DiligenceIQ to the test.
Run it against a deal you have already completed, or start with one workstream on one live transaction. Compare time saved, evidence coverage, analyst effort, finding quality and IC readiness.