Workpaper Automation
Prepare draft workpapers from approved policies, evidence and engagement files. Dotnitron builds around your templates, keeps source support visible and routes open items to reviewers.
What changes for your team
Teams repeatedly gather client files, map evidence and rebuild the same template before a reviewer can assess the conclusion. We connect those preparation steps to the firm’s methodology, then test whether drafts reduce effort and remain checkable.
Policy-to-control mapping, gap analysis, evidence review, ToD / ToE notes, diligence red flags, issue lists, and source-backed reporting can all be prepared for human review.
We do not replace your templates. We learn your control library, map your review process, and build workflows that draft into your exact workpaper format.
Workflows can run in private, client-approved environments with client data isolation, role-based review, audit trails, and controlled exports.
How it works
Agree on the work, information, business rules, user roles, desired output, and what the AI is allowed to do.
Bring in only the approved documents, records, business data, control libraries, or playbooks needed for the task.
Give your team findings, matrices, notes, data-backed answers, or work queues with sources and clear reasons for exceptions.
Track edits, accuracy, time saved, exception quality, and adoption before applying the system to more work.
Designed around your team
Teams with repeatable client delivery workflows and repetitive senior review bottlenecks.
Repeatable work that can be prepared with source citations before human review.
Reviewer-ready artifacts shaped to your templates, evidence standards, and client delivery format.
What your team sees in practice
Select one workpaper and define the reviewer standard.
Ingest representative policies, controls, evidence, data-room files, or prior workpapers.
Extract facts, map sources, and draft the first-pass workpaper sections.
Route outputs through reviewer approval and export to your template.
Controls that keep AI as a drafting layer and preserve professional judgment.
The conditions that make this work suitable for a focused first release.
Related ways to use it
Your first release
Prepare the agreed fields, findings and supporting references in your format. Mark missing, conflicting or unreadable material for the reviewer.
Give reviewers a way to inspect the support, edit the draft and record a decision. Professional conclusions and sign-off remain with your team.
Test source support, missing-evidence detection and reviewer corrections. Compare the preparation effort with the existing manual process.
For example, a policy-review workpaper could contain a control requirement, a cited policy passage, a coverage note and an open item. This is an illustrative output, not a claim about a delivered engagement.
Choose the right approach
| Approach | Useful when | Check before choosing |
|---|---|---|
| Audit or engagement software | Standard templates, workpaper storage and review routing cover the task. | Whether the product also prepares the evidence and analysis your reviewers need. |
| Document extraction tools | The main task is transferring consistent figures or fields from documents. | Source traceability, exceptions and how extracted data reaches the workpaper. |
| Custom preparation workflow | Your control library, evidence rules and client formats require a tailored process. | Reviewer acceptance, engagement isolation, citation quality and maintainable templates. |
Relevant client work
Our compliance and risk platform case study explains the end-to-end build, validation milestone and pending first end-client deployment. It demonstrates delivery experience, rather than a measured workpaper time-saving result.
Inspect the compliance platform case studyFAQ
No. We build around your methodology, templates, review standards, and client delivery formats.
We design the workflow to include supporting file, page, or paragraph references. Unsupported or unreadable material is flagged. Citation quality and completeness are tested with reviewers.
An automated workpaper is a draft prepared from approved inputs using software rules, extraction or AI. It can include supporting references, open items and review status in your template. The reviewer checks the evidence and owns the professional conclusion.
Audit or engagement software may already provide the templates and routing you need. A custom preparation workflow is useful when your methodology, source formats or integration requirements need a tailored implementation. We assess the existing tools before proposing a build.
We scope the required formats and test representative templates with your reviewers. The agreed export, source references and review history form part of the acceptance criteria.
Select representative workpapers and compare preparation time, supporting-source quality, missing-evidence flags and reviewer corrections with the manual baseline. Your reviewers define acceptance criteria before the build; an AI draft is not an audit opinion or a substitute for sign-off.
Technology partnership
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