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.

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.

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.

Agent Workflow Architecture

How the AI agent system works behind the page.

Every solution is implemented as a controlled workflow, not a loose chatbot. The agent operates inside approved data scopes, produces inspectable outputs, and routes judgment back to the right human owner.

Scope the job

Define the exact workflow, input sources, business rules, user roles, output format, and what the AI agent is allowed to do.

Retrieve the right context

Pull only approved documents, records, ERP context, control libraries, or playbooks before the agent drafts or acts.

Produce source-visible output

Generate findings, matrices, notes, SQL-backed answers, or queues with source references, exception reasons, and confidence signals.

Validate before expansion

Measure reviewer edits, pass/partial/fail outcomes, time saved, exception quality, and adoption before moving to adjacent workflows.

Workflow Scope

Built around the way your team already delivers work.

The workflow starts with one painful, repeatable use case, then expands only when reviewers and operators 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 serious business 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 successful 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 repeatable 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.