Measure BeforeYou Build
Every AI strategy begins with NINA.
Two assessments measure maturity, risk, and priorities, producing a validated prototype for AI Development. In five minutes, know where you stand. Delivered as a service, not software.
The process
Three-Phase Engagement
Three phases. Each validated before the next. From assessment to prototype in under three weeks.
AI Maturity Assessment
Online assessment measuring AI readiness across your organisation's key stakeholders. Results establish your baseline position.
Map data, model, and decision inventory
Identify governance gaps and control weaknesses
Quantify regulatory and operational risk exposure
Set baseline for Enterprise AI Readiness
AI Needs Planner
In-depth checkup with Nivara team. We assess current state, identify gaps, and map requirements for AI implementation.
Confirm business outcomes and decision owners
Align budgets, timelines, and risk appetite
Record assumptions, dependencies, and organisational constraints
Select candidate use cases for validation
Prototype Design
Visual prototype validating identified needs. Prepares handover to AI Development with User-Centred Design (ISO 13407).
Define accountability, escalation, and approval pathways
Specify human-in-the-loop workflows for high-risk decisions
Set logging, monitoring, and evidence requirements
Draft reference architecture for data and model flows
AI implementation framework
Methodology as Code
Outputs are written as configuration: control gates, ownership, evidence logs, and routing rules. Nivara OS enforces behaviour; RAIN compiles audit evidence.
It only takes 5 minutes
Benefits
Enterprise AI Readiness Capabilities
Six assessed capabilities, scored and documented for Enterprise AI Readiness.
Assess Maturity
Scores capability, data, governance, and risk across key stakeholders.
Map Risk
Maps 12 risk categories across six domains, with accountable owners.
Prioritise Use Cases
Ranks use cases by value, feasibility, data readiness, and governance effort.
Design Governance
Defines approval gates, evidence requirements, and audit trails for AI systems.
Assess Sovereignty
Checks residency, access controls, lineage, and retention against policy.
Plan Deterministically
Defines AI strategy, implementation plan, milestones, ownership, dependencies, controls.
Outcomes
Outputs You Can Execute
Executable artefacts: score, roadmap, governance, risk register, and timeline. Produced from assessment evidence, not slide decks.
01
AI Maturity Score
6-domain scorecard for Enterprise AI Readiness, with gaps and risk weighting.
02
Use Case Roadmap
Ranked roadmap for 90 days, with dependencies and governance checkpoints.
03
Governance Framework
Controls mapped to 12 risk categories, with evidence requirements and approval gates.
04
Operating Model Blueprint
Defined roles, RACI, and handovers for build, run, and oversight.
05
Risk Register
Risk register across 12 categories, with mitigations, owners, and residual ratings.
06
Implementation Timeline
A two-month timeline featuring key milestones, control gates, and resource allocation.
Approach
Why Start with a Methodology?
Most AI initiatives fail from missing baselines: no maturity benchmark, no risk map, no prioritised use cases. NINA is vendor-agnostic and scientific, then converts findings into configuration for Nivara OS. Methodology first. Execution second.
Discuss Your Results
Review your scorecard with a strategist. Confirm priorities, governance gates, and handover into AI Development.