01Worked example
Target screening sweep
Run a first-pass screen over a list of targets with one rubric. Each company gets the same five-question pass and the same length, so the comparison is apples-to-apples rather than whoever-had-time-to-dig.
Use case · For deal teams
AI for due diligence that stays consistent.
Inconsistency is the bug; a repeatable workflow is the fix. Run the same question set, source breadth and output length across every target in a pipeline, and keep each finding traceable to the document it came from.
DiligenceFinanceLegal
04
In access today
04
Moves
02
Workflows
Working note · deal teamscited
Apply one rubric to every target[1]
Read the document room[2]
Check the public record[3]
Keep the trail[4]
[1] Research[2] Search[3] News[4] Storage
The stack under the work
The workspaces this job runs on.
Listed in the order the work moves through them, each carrying its live status.
Starts hereAvailable
Research
Notebooks that read, synthesise and reference. Branch, version, merge — turn a question into a defensible answer.
Open ResearchWhat you can do
Four moves, one workspace.
The concrete work behind "ai for due diligence" — not a feature list.
/01
Apply one rubric to every target
Branch the same diligence question set per company so each gets the same depth — no target gets the thin treatment.
/02
Read the document room
Upload the data-room files and search across them semantically; pull the clause or figure, not the 200-page PDF.
/03
Check the public record
Sweep deduped news clusters for litigation, leadership churn and the stories that don't make the management deck.
/04
Keep the trail
Every finding lands in versioned storage with its source attached — the diligence file defends itself in a later review.
What it reads against
Finance work is only as good as its sources.
The reference collections this job draws on. Each is a page you can open and read before you trust a single answer.
Collections are libraries the workspaces read from, kept as what they are rather than flattened into one pile. See the full collection breakdown.
Example workflows
What it looks like end to end.
Red-flag pass
Before the IC, run a focused red-flag pass — litigation, related-party transactions, going-concern language and adverse press — with each flag linked to the page or article that raised it.
Questions
Frequently asked.
Different job? Browse every use case or start from your industry.
Can askFinz read a data room?
Upload the data-room documents and they become a searchable index; you can ask questions across the whole set and get back the specific clause or figure with its source.
How does it keep diligence consistent across targets?
You run the same question set as a repeatable workflow, so every target gets the same rubric, source breadth and output length — consistency is enforced by the workflow, not by memory.
Is the output auditable?
Yes. Findings are stored with their source documents attached and versioned, so a reviewer can trace any conclusion back to the page it came from.
For deal teams
Put it to work.
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- reference collections
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