Know the conditions around AI before deciding what to build.
The ECV AI–Data Convergence Framework connects portfolio direction, reusable capability, controlled operation and evidence before technology commitments are made. DAIS helps teams describe the conditions around useful AI.
- 01Owned context
Start with an owned outcome: one bounded workflow, one decision owner and a measurable change.
- 02Cumulative readiness
Connect reusable capability: data products, evaluation, contracts, integration and platform services. Strong areas never hide a necessary missing condition.
- 03Portable result
Operate with live assurance: identity, human control, evidence, recovery, learning and exit. Keep the profile and context together.
Explore DAIS in five focused views.
Choose the question you need to answer: reported practice, enterprise architecture, capability foundations, adoption governance or the next ECV engagement.
- 01
Framework
Understand the four domains, shared Level 0–4 scale, bottleneck formula and treatment of unknowns.
Continue - 02
Architecture
See how governed facts become bounded AI actions and operating evidence.
Continue - 03
Capabilities
Explore the capabilities that connect an owned workflow to a controlled effect.
Continue - 04
Adoption
Govern one use case from framing and proof through controlled operation, expansion and retirement.
Continue - 05
Work with ECV
See where self-service DAIS ends and a separately scoped engagement can begin.
Continue
A result you can carry forward.
Twenty-one practice questions describe Data, AI, Integration and Assurance. The result keeps this D/A/I/S profile, explicit unknowns and declared constraints together. Overall readiness is the minimum of the four classified domains; each saved result explains its version-specific domain calculation.
DAIS does not generate a customer roadmap or deployment recommendation.
- Self-reported profile
- Four separate views with uncertainty kept visible.
- PDF report
- A readable snapshot for stakeholders.
- Markdown context pack
- Portable context for continued private discovery.
Start with what is true today.
Record one bounded AI-enabled use case, then decide what deserves deeper validation. This public learning edition includes synthetic demo profiles. Saving assessments and exporting personal results require the separate full application.