AI Solutions
AI solutions built for the reality of regulated organizations.
We design, integrate and deploy AI solutions through PMAIS — a phase-and-gate methodology that connects business value, regulatory obligations, data governance, human oversight, technical validation and continuous monitoring.
Book a Discovery CallBeyond the model
AI implementation is more than model selection.
An AI system can be technically functional and still be unsuitable for production. Before deployment, we determine what the organization is required to satisfy — legally, regulatorily, contractually and operationally — and translate those obligations into implementation controls and evidence.
Business
Risk
Regulation
Data
Technology
People
Regulatory & jurisdictional assessment
We map the obligations that actually apply.
Determined per engagement, based on jurisdiction, sector, use case, data and the organization's role in the AI supply chain.
European Union
- EU AI Act
- GDPR
- Sector-specific requirements
- Cross-border data considerations
Canada
- PIPEDA (federal)
- Quebec's Law 25
- Other provincial privacy regimes
- Sector-specific obligations
- Treasury Board Directive on Automated Decision-Making (public sector)
United States
- Federal requirements and FTC consumer-protection considerations
- Sector-specific regulation
- State privacy and AI laws
- NIST AI Risk Management Framework
International
- Applicable local privacy, AI, cybersecurity and data-transfer requirements
- Assessed per engagement, including Australia
Regulatory information is provided for general informational purposes and does not constitute legal advice. Applicable requirements are assessed based on the specific organization, jurisdiction, sector, AI system and use case. Legal counsel may be engaged where appropriate.
Data governance & residency
Every dataset has a documented path.
- Classification
- Location
- Processing
- Storage
- Backup
- Logging
- Retention
- Deletion
Before deployment, PMAIS identifies the data involved, its classification, permitted processing purposes, retention requirements, residency constraints, cross-border transfers, subprocessors, model-provider data practices, logging requirements and deletion obligations — then translates them into technical and contractual deployment controls.
PMAIS implementation controls
Seven artifacts that make a deployment defensible.
Risk Classification & Regulatory Crosswalk
The applicable AI risk tier and the specific obligations that apply, mapped to controls.
Human Oversight Plan
Where AI can act, where human review is mandatory, and who holds decision authority.
Data Governance Record
Data lineage, classification, consent basis and residency configuration.
Test & Validation Evidence Package
Accuracy, robustness, safety, security and domain performance testing before production.
Rollback / De-escalation Plan
A rehearsed path to reduce autonomy or withdraw the system without disrupting the process it supports.
Monitoring & Incident Log
Retained continuously post-deployment.
Stage-Gate Review Record
The accountable approver and evidence at each PMAIS gate.
Human oversight
AI drafts. Humans decide.
AI may recommend, summarize or accelerate. Humans remain accountable for decisions that require human judgment, and every AI-generated artifact carries a named human reviewer of record.
Continuous governance
Assessment is a lifecycle activity, not a checklist.
- Deploy
- Monitor
- Revalidate
- Change
- Reapprove
- Retire
Regulatory requirements evolve, and so does the deployment record. PMAIS treats regulatory assessment as a lifecycle activity rather than a one-time checklist.
Technology partners
What we require of every technology partner.
- Documented data-handling, residency and retention commitments.
- Data retention and deletion policies.
- Model training / data-use policy.
- Subprocessor transparency.
- Change notification for material model or behaviour updates.
- Support for logging and evidence extraction compatible with PMAIS gates.
- Security and access-control information.
- Willingness to participate in independent testing, validation or incident investigation where the sector requires it.
Reference
What we assess.
| Dimension | What it covers |
|---|---|
| Jurisdiction | Where the organization, user, data and AI service are located. |
| Sector | Industry-specific obligations. |
| AI use case | What the system actually does. |
| Risk | Potential harm from failure or misuse. |
| Data | What enters, leaves or is generated. |
| Residency | Where data is stored, processed, backed up and logged. |
| Privacy | Collection, use, disclosure, consent and transparency rules. |
| Security | Controls and threat considerations. |
| Human oversight | Which decisions must remain human-controlled. |
| Vendor | What the model or provider retains, processes or changes. |
| Evidence | What must be documented. |
| Lifecycle | How the system is monitored, changed and retired. |
Standards referenced
The frameworks we work against.
PMAIS considers the applicable combination of legislation, regulation, standards, contractual obligations and organizational policy. Depending on the engagement, this may include the NIST AI Risk Management Framework, ISO/IEC 42001, ISO/IEC 23894, ISO/IEC 27001 and ISO/IEC 27701.
Referenced as working frameworks. RN Consultants does not claim certification against any of these standards.
Sector examples
What tends to dominate the control set.
Aerospace
Airworthiness, safety, quality, cybersecurity, traceability.
Financial Services
Model risk, privacy, financial regulation, auditability.
Telecom
Privacy, security, customer data, operational resilience.
Government
Privacy, public-sector information, procurement, accountability.
The exact control set for your organization is determined during the PMAIS regulatory crosswalk.
Closing statement
The difficult part of enterprise AI isn't making the model work. It's making the entire system acceptable to the organization that has to operate, govern, audit and defend it. PMAIS is designed around that problem.
AI Solutions pricing
From focused automation to governed enterprise AI. Pricing depends on integration complexity, risk classification, regulatory requirements, data environment and governance scope.
| Engagement | Scope | Pricing basis |
|---|---|---|
| Focused automation | A single bounded process or task-scoped agent with defined inputs, outputs and exclusions. | Fixed fee, agreed before work starts. |
| Governed diagnostic | Use-case inventory, risk classification and regulatory crosswalk delivered as a costed roadmap. | Fixed fee for a four to six week engagement. |
| Regulated delivery | End-to-end PMAIS implementation with validation evidence, oversight design and monitoring. | Milestone-based, priced and invoiced per PMAIS gate. |
| Platform & continuous governance | Platform access, revalidation cycles and regulator-facing advisory support. | Annual subscription and/or monthly retainer. |
Indicative structures. Exact figures are confirmed in a written proposal after the discovery call.
Next step
Bring one real use case to a discovery call.
Thirty minutes with your risk, compliance and technology leadership.