Your AI is live. The documentation to govern it isn't.
When AI goes into production, three things almost always stay behind: a documented human review process, SOPs for what the AI produces, and compliance mapping for the obligations it triggers. That gap is what we close.
What's Included
AI Remediation engagements are scoped to your specific implementation – the tools deployed, the processes they touch, and the compliance frameworks that apply. The deliverables follow a consistent structure built around the post-implementation gap most organizations leave open.
AI Process Mapping
We map every business process touched by the AI – upstream and downstream. What data goes in, what outputs come out, who receives them, what decisions or actions they trigger, and where human review currently occurs (formally or informally). This mapping is both the foundation for all subsequent work and a critical standalone deliverable most organizations lack entirely.
Human-in-the-Loop Workflow Design
For every AI output that requires human validation, we design and document the review workflow: who performs the review, what they're looking for, how they record it, what happens when output is rejected or escalated, and within what timeframe. The result is a tamper-evident, auditable record of oversight – not a person glancing at a screen.
Standard Operating Procedures (SOPs)
Every operational step that intersects with the AI implementation gets a written SOP – practical, step-by-step guidance written for the people doing the work. How to interpret and act on AI outputs, what to do when output appears anomalous, how to document exceptions and escalations, and how to handle system downtime without breaking the compliance process.
Compliance Gap Documentation
We conduct a compliance mapping exercise for each AI use case – identifying which regulatory requirements apply to the data and decisions the AI touches. For SOX-relevant processes this includes control design documentation for AI-adjacent ICFR controls, evidence capture procedures, segregation of duties mapping, and change management documentation for any process changes the AI drove.
Policy & Procedure Updates
AI implementation typically triggers a cascade of required updates to existing documentation. Policies governing financial data, information security, change management, and vendor risk may all need to reflect the introduction of AI into the processes they govern. We identify every affected document and update them – so your documentation estate is consistent with how you now operate.
Training Documentation & Rollout Support
The most carefully designed human-in-the-loop process fails if the people responsible for it don't understand their role. We develop role-specific guides for reviewers, approvers, and escalation owners – plus quick reference cards, exception handling guides, and onboarding documentation so new team members can be trained consistently.
The Post-Implementation Gap
When an AI tool is deployed into a business process, the technology gets implemented, the vendor demos it, IT signs off, and leadership celebrates the efficiency gains. Then operations inherits a system that produces outputs no one has a documented process to handle, validate, or act on.
Three things are almost always missing after deployment:
The human review layer is informal or absent
Someone is probably reviewing AI outputs – but there's no documented process for how, by whom, within what timeframe, under what criteria, and with what sign-off. An informal habit is not a control. It cannot be tested, evidenced, or defended in an audit.
Operations has no SOP for what the AI produces
Even when AI is in production, the downstream workflows – what happens after the AI generates an output – are often undefined. Teams adapt informally, inconsistently, and without documentation.
Compliance obligations tied to AI outputs aren't mapped
If AI touches financial data, credit decisions, customer records, or regulated processes, there are compliance requirements attached. An AI workflow that reads financial records to support a quarterly analysis is touching SOX-relevant data – most organizations haven't mapped that exposure.
How It Works
Every engagement begins with process mapping and scopes to your specific AI implementation – the tools, the workflows they touch, and the compliance frameworks that apply.
Discovery & Mapping
We map every business process touched by the AI – inputs, outputs, downstream decisions, current human review (formal or informal), and applicable compliance frameworks.
Gap Assessment
We identify what's missing: undocumented review workflows, absent SOPs, unmapped compliance obligations, and policies that haven't been updated to reflect how the organization now operates.
Documentation
We write the human-in-the-loop workflows, SOPs, compliance control documentation, and updated policies – in your organization's voice, specific to your AI implementation.
Rollout & Handoff
We develop training materials for affected teams and hand off a complete, governance-ready documentation package that functions as a book of record – not a filing cabinet.
SOX and the Human Validation Requirement
SOX compliance is one of the clearest examples of why AI implementation without documentation creates immediate regulatory risk. Under SOX Section 404, organizations must establish, document, and maintain internal controls over financial reporting (ICFR).
When AI enters a financial process – generating journal entries, supporting reconciliations, processing financial data, assisting with MD&A reporting – those AI outputs often touch data that SOX requires to be validated by a human before it enters the book of record.
That validation layer must be more than a person glancing at a screen. It must be a documented, testable process: who reviews the AI output, what they are reviewing for, what criteria trigger escalation, and how their review is recorded as evidence. We create all of it – end to end.
The AdventuReliable Difference
AI remediation is a change management and documentation problem, not a technology problem. Most organizations try to address it through their technical teams – who understand the AI but aren't documentation specialists – or through their auditors, who identify the gap but don't write the fix.
We bring change management thinking to compliance documentation. We understand that deploying AI without the governance layer isn't just an audit risk – it's an operational one. And we know how to build the documentation that makes the governance layer real.
Who We Serve
AdventuReliable serves clients across the Greater Toronto Area and Ontario, with deep experience in federally regulated financial services, banking, and organizations subject to SOX compliance requirements. We work with organizations that have AI running in production but the human-in-the-loop process, the SOPs, and the compliance documentation aren't yet in place – as well as organizations that are mid-implementation and want to build the governance layer before the technology goes live.
Don't wait for the audit to surface what's missing.
If your AI is running in production without the human-in-the-loop processes, SOPs, and compliance documentation in place, the time to act is before the next review cycle – not during it.