AI readiness roadmapFrom mapped knowledge to AI that does the work
Ready for AI, step by step, with people in control.
AI works on what the company really is. We map it first, connect what we map into one knowledge model, and only then put agents to work, with controls and human gates.
The roadmapFour stages, from mapping to agents
From mapped knowledge to agents that run the work.
Read left to right: knowledge modules feed one knowledge hub; the hub forms a live model of the company; function-specific agents work on that model.
1 · Knowledge modules
- Process mapping
- Data governance mapping
- From the diagnosis
- Decision mapping
- Roles and responsibilities
- Applications and infrastructure
- Organization and workforce
- Financial and economic
2 · Knowledge hub
Corporate knowledge hub
One connected, always-current model
- Processes
- Data governance
- Decisions
- Roles
- Applications
- Organization
- Financial
3 · Organization model
Organization model
A live model of how the company works
4 · AI agents
- SalesPipeline, quotes, follow-ups
- MarketingCampaigns, content, segments
- FinanceClose, invoices, controls
- OperationsPlans, orders, exceptions
A named person approves before anything goes live
AssessmentWhat the readiness assessment covers
Design best practice for the AI age.
Step 01: AI-readiness assessment
Which processes and data are ready for AI, and which must be fixed first.
Readiness register
Step 02: Best-practice redesign
The target processes and data governance an AI can safely work on.
Target design
Step 03: Controls and human gates
Where a named person approves, before anything goes live.
Control specification
DeploymentWhere the platform runs
Architecture that meets the data where it lives.
- Maximum isolation
On-premise
On your own servers.
- Dedicated boundary
Private cloud
In your own tenant.
- Selective federation
Hybrid
Workloads split by sensitivity.
- Country control
Sovereign
Inside the jurisdiction.
A prerequisite for regulated, sensitive and sovereign environments.