● AI-READY DATA ASSESSMENT

Know if your data can support trusted AI before you scale.

A decision-grade assessment of the data, architecture, controls and operating model behind your AI ambitions—translated into a practical investment roadmap.

Request an assessment ↗
12
CONNECTED DOMAINS
ASSESS → PRIORITISE → DESIGN → DELIVER

THE REAL QUESTION

Is the system ready—not just the model?

AI initiatives often begin with a model demonstration and discover the hard problems later: unclear ownership, stale data, weak retrieval, missing access controls, unmeasured quality and no operational response.

We examine the full evidence path from source to answer, giving executives and engineering leaders one view of risk, readiness and next action.

THE ASSESSMENT FRAMEWORK

Twelve domains. One production system.

Each domain is evaluated through evidence, stakeholder interviews and architecture review—not questionnaire optimism.

01

Strategy & use-case fit

Value, decision boundaries, risk appetite and success criteria.

02

Data contracts & freshness

Ownership, schemas, completeness, timeliness and lineage.

03

Content preparation

Parsing, metadata, chunking and document lifecycle.

04

Embeddings & model lifecycle

Selection, versioning, drift and reproducibility.

05

Retrieval quality

Hybrid search, filtering, reranking and citations.

06

Semantic layer & analytics

Definitions, metrics and text-to-SQL safety.

07

Agents & tool controls

Permissions, memory, orchestration and approval.

08

Security & access

Identity, isolation, encryption and least privilege.

09

Evaluation & guardrails

Golden datasets, thresholds and adversarial tests.

10

Observability & response

Traces, incidents, rollback and runbooks.

11

Cost & capacity

Economics, latency budgets, caching and demand.

12

Delivery & operating model

Testing, release gates, accountability and skills.

MATURITY MODEL

A score leaders can act on.

0

Exploratory

Use cases and data remain informal.

1

Fragile

Pilots depend on individual knowledge.

2

Governed

Ownership exists; production gaps remain.

3

Production-ready

Controls and operations support deployment.

4

Optimised

Quality and cost improve continuously.

WHAT YOU RECEIVE

From evidence to an executable roadmap.

01

Executive readiness scorecard

Maturity, dependencies and decisions across all domains.

02

Prioritised risk register

Failure modes, impact, likelihood, ownership and controls.

03

Target architecture

Sources, context, models, policies and telemetry.

04

Control & evaluation framework

Quality gates, security, tests and release evidence.

05

90-day action plan

Sequenced quick wins and accountable outcomes.

06

Investment case

Options, trade-offs and a production-readiness path.

HOW IT WORKS

01

Discover

Align outcomes, scope and decisions.

02

Review evidence

Inspect data, architecture and controls.

03

Assess & score

Identify the highest-impact constraints.

04

Playback & plan

Agree priorities, ownership and investment.

START WITH THE EVIDENCE

Turn AI uncertainty into a focused plan.

Request an assessment ↗