Evidence piles up fast
Advisory teams can receive 200 or more evidence files for a single engagement, each requiring manual inspection against control requirements and testing criteria.
Evidence Review
Evidence review automation for advisory engagements.
Review hundreds of client evidence files against control requirements, flag weak support, and draft source-backed reviewer notes.
Workflow Value
From dense data to defensible action.
AI reviews evidence against the requirement
The workflow reads the control, request list, testing objective, and uploaded evidence, then checks whether the file supports the requirement.
Weak support is flagged early
Missing, stale, incomplete, contradictory, or irrelevant evidence is surfaced before senior review, with notes explaining the concern.
Reviewers get draft notes, not black-box answers
The output is a set of reviewer-ready observations with citations and confidence signals that your team can approve or revise.
Workflow Scope
Built around your engagement delivery process.
The workflow starts with a narrow advisory use case, then expands only when reviewers trust the source-backed output.
Who this is for
Teams with document-heavy client delivery workflows and repetitive senior review bottlenecks.
- Audit support teams
- Cyber compliance firms
- Risk advisory teams
- GRC consultants
What we automate
Repeatable work that can be drafted with source citations before human review.
- Evidence intake
- Control requirement matching
- Weak support detection
- Exception note drafting
- Reviewer queues
Outputs
Reviewer-ready artifacts shaped to your templates, evidence standards, and client delivery format.
- Evidence sufficiency summaries
- Missing evidence reports
- Exception drafts
- Source-backed review notes
Delivery Design
What the workflow looks like in practice.
Each solution page breaks the buyer workflow into operating steps, reviewer controls, and pilot-fit criteria a real advisory team would ask about.
01
Ingest evidence files, request lists, controls, and testing objectives.
02
Classify files by control, system, period, and support type.
03
Flag missing, stale, weak, contradictory, or irrelevant support.
04
Draft reviewer-ready notes with source references and exception categories.
Reviewer controls
Controls that keep AI as a drafting layer and preserve professional judgment.
- Evidence-by-control queue
- Missing and weak support flags
- Reviewer override tracking
- Source-backed observations
Good pilot fit
Signals that this workflow is ready for a focused 30-day pilot.
- Evidence volume is high
- Client back-and-forth is frequent
- Support requirements are documented
- Senior review time is spent on source-checking
Related Workflows
Where teams usually expand next.
Most advisory pilots start narrow, then expand into neighboring workflows once reviewers trust the output.
FAQ
Frequently asked questions
Can it review evidence across many file types?
Yes. We can design workflows for PDFs, images, spreadsheets, policy docs, tickets, exports, and screenshots.
Does AI decide pass or fail?
No. AI drafts review notes and flags issues. Your reviewers make the final call.
Automate one advisory workflow.
Bring the workpaper, evidence review, or diligence process that consumes the most hours. We will map a practical AI-assisted pilot around your methodology.