A source-linked deal brief
Prepare a first draft from approved material, with references and open questions for the reviewer.
Services 04
We put AI to work inside real workflows rather than in a chat window on the side: drafting, summarising, extracting and sorting where it genuinely saves hours. Everything ships with guardrails, and anything that leaves the firm passes through human review first.
Why it matters
The value of AI is in the workflow, not in another chat window.
Most firms have tried the chat tools and found the same thing: impressive on a good day, unreliable on a bad one, and disconnected from where the work actually happens. Copying context in and pasting drafts out is its own kind of admin, so usage fades after the first month.
We build AI into the workflow instead: the first pass of a teaser drafted from your template and the source material, a data room summarised into a checkable table, an inbox triaged before the morning meeting. The person stays in charge of everything that matters; AI handles the mechanical drafting that comes before those judgements.
How we approach it
How we deliver this service.
01
Drafts, not decisions
AI produces first passes for a person to review, edit and sign off. Nothing it writes leaves the firm on its own.
02
Grounded in your documents
Agents work from your templates, your files and your data, with sources shown, rather than answering from a model's general knowledge.
03
Honest about limits
Where AI is not reliable enough for a task, we say so and build a conventional automation instead. A wrong answer delivered confidently is worse than no answer.
What this covers
What this looks like in practice.
01
First drafts of teasers, profiles and summaries
First passes produced from your templates and source documents, ready for a person to edit.
02
Document review and data extraction
Key terms and figures pulled out of long documents into structured, checkable form.
03
Meeting and call notes
Discussions captured into notes and actions and filed against the right deal.
04
Inbox triage and routing
Incoming mail sorted by deal and by urgency, so nothing important sits unread.
05
Buyer research and list enrichment
Candidate buyers researched and profiled faster, with sources shown for checking.
06
Human review steps built into every output
Nothing drafted by AI leaves the firm without a person signing it off.
Project examples
Projects we can scope around your tools.
Document review and extraction
Pull key terms and figures into a structured view that a person can check against the originals.
Meeting notes to deal actions
Turn an approved transcript into a draft note and proposed actions for your team to confirm.
Inbox triage
Suggest the mandate and priority for incoming messages, with clear review rules for uncertain cases.
Scope
What this covers, where it runs and how it is maintained.
What do AI agents actually do inside a deal workflow?
They produce first passes for a person to review: teasers, company profiles and summaries drafted from your own templates and source documents; key terms and figures extracted from long documents into structured, checkable form; meeting and call notes captured into actions and filed against the right deal; incoming mail triaged by deal and by urgency; and candidate buyers researched and profiled with sources shown for checking. Agents work from your templates, your files and your data rather than a model's general knowledge. Every output ships as a draft with a human review step built in, and nothing drafted by AI leaves the firm without a person signing it off.
How does Verdalyze keep AI output reliable?
By deploying it only where the cost of reviewing a draft is small next to the time it saves, and avoiding it where that trade does not hold. Accuracy depends on the task, which is why the rule is drafts, not decisions: AI handles the mechanical drafting that comes before a judgement, and the person stays in charge of everything that matters. Where AI is not reliable enough for a task, we say so and build a conventional automation instead, because a wrong answer delivered confidently is worse than no answer. Models are chosen to fit the task and the firm's constraints, and built so they can be swapped as the landscape moves.
Does client data train the models?
No. AI features are configured under terms that exclude training on your data. Data is handled securely and privately, and we agree which providers process it, where it is processed and the access required for the workflow. Deployment within your own environment is available where appropriate.
At a glance
Which tool fits which task.
| Task | Tool that fits | Why |
|---|---|---|
| Filing a signed NDA against the right mandate | Automation | The rule can be written down in advance, so it behaves the same way every time. |
| Drafting a teaser from your template and source documents | AI agent | The material varies, the output is a draft, and a person signs it off. |
| Moving a deal to the next stage and opening its checklist | Automation | No judgement is involved, and a rule that fails produces an error rather than a plausible wrong answer. |
| Summarising what is unusual in a data room | AI agent | Judgement over messy material, with each figure traced to its source page for checking. |
| Chasing an outstanding signature | Automation | High frequency, low judgement, and easy to verify. |
| Extracting key terms from a stack of NDAs | AI agent | Documents vary in format, and the output is structured and checkable. |
Common questions
Questions about this service.
Does our client data train the models?
No. Client information is never used to train external models. AI features are configured under terms that exclude training on your data, and the same rule applies to our own tooling.
How accurate is it?
It depends on the task, which is exactly why every output ships as a draft with human review built in. We deploy AI where the cost of reviewing a draft is small next to the time it saves, and we avoid it where that trade does not hold.
Which models do you use?
Whichever fit the task and your firm's constraints; that is part of the assessment rather than a fixed answer. We build so that models can be swapped as the landscape moves, because it moves quickly.
Further reading
Essays on the thinking behind this service.
Related services
Work that usually goes with this.
Working with sensitive information
Built around the way your firm already works.
Your VDR remains the source of truth for shared deal documents. We agree what each system needs to access, where information is processed and how the build fits your firm's existing setup.
Agreed for each engagement.
Your document environment stays yours
We build around the VDR and tools your firm already uses, keeping them as the source of truth for shared deal documents.
Only the context the work needs
Before a build, we agree what information the system uses, who can access it and how it moves between your existing tools.
A deployment agreed together
Hosting and data handling are shaped around the engagement and your firm's requirements, including your own environment where appropriate.
What is slowing your team down?
Tell us how your firm runs deals. We will help you identify the first useful system to build.
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