Access and control
- Role-based access controls
- Human approval workflows
- Content filtering
- Data retention controls
Intelligent Automation
Trust designed in from the first release.
The controls that make AI safe to deploy in a real organization: permissions, approvals, monitoring, logging, evaluation, and clear rules for what the system may and may not do.
- Fixed-scope discovery before any build commitment
- Integrates with the systems you already run
- Human approval on the actions that matter
- Measured after launch, not just at handover
The business problem
Why organizations ask for this.
AI moves from pilot to production the moment it can be trusted with real data and real customers. Governance is what makes that step defensible to a board, a regulator, and your own team.
Capabilities
What is included.
Assurance
- AI governance frameworks
- Data privacy design
- Risk assessments
- Security reviews
Monitoring
- Audit logging
- Output monitoring
- Prompt injection protection
- Hallucination evaluation
Use cases
Where it earns its place.
Representative examples of how this service is applied. Your version starts from your own process, systems, and constraints.
- An AI usage policy and approval process for a growing organization
- Access controls mapped to existing roles before a copilot rollout
- An evaluation process for answer accuracy and refusals
- Logging and reporting that satisfies internal audit
- Protection against prompt injection in customer-facing agents
- Retention and privacy rules applied to transcripts and prompts
Integrations
Connects to what you already run.
Elevariq selects models, platforms, and infrastructure according to security, scalability, cost, integration, and ownership requirements.
- Salesforce, HubSpot, Zoho, Microsoft Dynamics
- SAP, Oracle, Odoo and custom ERP
- Microsoft 365 and Google Workspace
- Slack and Microsoft Teams
- ServiceNow and helpdesk tools
- Accounting and finance platforms
- HR and recruitment platforms
- Shopify and WooCommerce
- Data warehouses and BI tools
- Custom databases and internal APIs
Delivery approach
Six stages, defined deliverables.
- Stage 01
Discover
Document the current process end to end, including the exceptions people work around.
- Stage 02
Design
Model the target workflow, decision rules, approvals, and measurement plan.
- Stage 03
Build
Develop the automation, extraction logic, or model, and test against historical cases.
- Stage 04
Integrate
Connect source and destination systems with the right permissions and error handling.
- Stage 05
Launch
Run in parallel with the manual process until accuracy and coverage are proven.
- Stage 06
Optimize
Review exceptions, expand coverage, and retrain or re-tune on a schedule.
Controls & quality
Built to be trusted in production.
Security, permissions, and human oversight are designed in from the first release rather than added after something goes wrong.
Permission mapping
Automations inherit the access rules of the systems they touch.
Exception queues
Anything the workflow cannot confidently handle is routed to a person.
Approval checkpoints
Financial, legal, and customer-facing steps can require sign-off.
Full audit trail
Each run records inputs, decisions, outputs, and who approved what.
Confidence thresholds
Low-confidence extractions and predictions are flagged, not applied silently.
Rollback and re-run
Failed steps can be retried or reversed without corrupting records.
Questions
AI Governance, answered.
Which frameworks do you work to?
We align to recognised risk-management and privacy practice and to your sector's requirements, then document the controls in language your auditors can follow.
Can you review a system we already built?
Yes. An independent review of an existing deployment is a common starting point.
Is governance worth it at our size?
Proportionately, yes. A small organization needs fewer controls, but it still needs to know what the system can access and who approved it.
How does an engagement start?
With a strategy conversation about the problem, the systems already in place, and the outcome you need. If the scope is unclear, we run a short assessment first and come back with options.
Can we start small?
Yes. Most clients begin with one focused use case, prove it works, and expand from there rather than committing to a full programme up front.
NEXT STEP
Ready to talk about ai governance?
Tell us what is happening today, what it costs you, and what a better version would look like. We will come back with a practical next step.
Your first conversation focuses on the problem, feasibility, priorities, and potential business value.