Assessment
- AI-readiness assessments
- Automation audits
- Use-case discovery
- Process mapping
- Data-readiness analysis
Intelligent Automation
Decide what is worth building.
A structured assessment of where AI and automation will actually pay back in your organization, with feasibility, data readiness, cost, and sequencing set out clearly enough to act on.
- 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.
The hard part is rarely the technology. It is choosing which of thirty possible use cases to fund first, and knowing which ones your data and processes can genuinely support today.
Capabilities
What is included.
Planning
- AI roadmaps
- Feasibility studies
- ROI analysis
- Vendor evaluation
- Technology selection
- Proof-of-concept planning
Adoption
- Governance planning
- Adoption strategy
- Employee AI training
- Change communication
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.
- A leadership team choosing between competing AI proposals
- An operations review identifying the highest-cost manual processes
- A feasibility study before committing to a build
- A twelve-month roadmap sequenced by value and readiness
- A vendor comparison for a platform decision
- Practical AI training for teams expected to use the tools
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 Strategy, answered.
What do we get at the end?
A prioritised use-case list, feasibility and data notes for each, indicative cost and effort, a sequenced roadmap, and a recommended first project.
Are you independent about technology?
Yes. We have no resale incentive, and platform recommendations are made against your requirements.
How long does an assessment take?
Typically two to four weeks depending on the number of departments and systems involved.
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 strategy?
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.