Each control repeats the same review pattern
Teams read the control description, inspect policy and procedure documents, review evidence, then write assessment notes for design and operating effectiveness.
ToD / ToE Support
AI support for Test of Design and Test of Effectiveness workflows.
Draft control-by-control ToD and ToE assessments from control descriptions, client documentation, and evidence for human reviewer approval.
Workflow Value
From dense data to defensible action.
Draft Test of Design assessments
AI reads the control objective, risk, policy language, and process documentation, then drafts whether the control appears designed to mitigate the stated risk.
Draft Test of Effectiveness notes
AI reviews evidence samples and operating records to draft whether the control appears to have operated consistently during the period.
Exceptions go to human reviewers
Potential exceptions, unsupported claims, missing samples, or inconsistent evidence are routed to reviewers with source references.
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.
- IT audit teams
- SOC 2 advisory teams
- GRC consultants
- Internal control review teams
What we automate
Repeatable work that can be drafted with source citations before human review.
- Control context assembly
- ToD draft notes
- ToE draft notes
- Exception flagging
- Reviewer approval flows
Outputs
Reviewer-ready artifacts shaped to your templates, evidence standards, and client delivery format.
- ToD assessment drafts
- ToE assessment drafts
- Exception summaries
- Source-backed control 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
Bring together control descriptions, risk statements, policies, procedures, samples, and evidence.
02
Draft Test of Design notes from the control context and supporting documentation.
03
Draft Test of Effectiveness notes from operating evidence and sample support.
04
Escalate exceptions, unsupported claims, and inconsistent evidence for reviewer approval.
Reviewer controls
Controls that keep AI as a drafting layer and preserve professional judgment.
- Separate ToD and ToE draft areas
- Exception and sample issue flags
- Assessment language matched to firm style
- Reviewer approval history
Good pilot fit
Signals that this workflow is ready for a focused 30-day pilot.
- Controls repeat across engagements
- Testing criteria are explicit
- Evidence samples are available
- Reviewers spend time rewriting junior notes
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 the assessment language match our firm style?
Yes. We train the workflow around your phrasing, review conventions, and workpaper format.
Can reviewers override AI drafts?
Yes. Human review, editing, and approval are core parts of the workflow.
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.