How long does the engagement take?

Five weeks from kickoff to a final foundations plan. The scope is fixed and the deliverable dates are fixed.

Will you recommend a specific platform?

Only when it is essential to the outcome. Where a platform call is needed (for example, a warehouse or governance layer), we say so and explain the trade-offs. We carry no resale or referral incentive.

Can you also deliver the remediation work?

Yes. Once the roadmap is approved, we can engage on the build and integration work. There is no obligation to continue with us.

How do you handle Australian privacy and AI regulation?

The governance framework is built on Australian privacy law and the evolving AI regulatory environment. Data sovereignty is a default, not an upsell.

What if our data is in worse shape than we admit?

That is the expected starting point. The audit is honest by design. The output reflects reality and the roadmap is sequenced to make the work tractable.

Plan · Service 03

DataStrategy&Foundations. Getthedatarightbeforeyouspendonthemodel.

A Data Strategy & Foundations engagement audits the data your business already holds, identifies the gaps that would block AI delivery, and produces a sequenced plan to fix them. Most AI projects fail at the data layer. This is the work that makes the rest of the roadmap deliverable.

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Australian data sovereignty by default

Production-grade architecture

Roadmap, not just a report

What we deliver

A data foundation your AI can actually run on. Audited, sequenced, fundable.

Five concrete artefacts that move you from a fragmented data landscape to one your AI initiatives can rely on. Operational outputs, not theoretical frameworks.

Data Landscape Audit

A documented map of every system, source, and silo where business-critical data lives. We identify ownership, quality, refresh cadence, and the integration points that matter for AI.

Data Quality & Readiness Score

Each high-priority dataset is scored against a consistent rubric for completeness, accuracy, accessibility, and structure. You get an honest read on what is AI-ready today and what is not.

Reference Architecture

A target-state architecture for storage, integration, governance, and access. Tool-agnostic where possible, with explicit recommendations where a platform call is needed.

Governance & Privacy Framework

Roles, policies, and controls aligned to Australian privacy law and emerging AI regulation. Covers consent, retention, access, vendor handling, and audit obligations.

Foundations Roadmap

A sequenced twelve-month plan covering remediation, integration, and capability work. Each item carries an owner, an investment range, and a dependency map against your AI roadmap.

Quick Wins Backlog

A short list of high-leverage, low-cost fixes that unlock immediate value. Most clients ship the first three within sixty days of the engagement closing.

Our strategic process

A five-week engagement. Foundations you can build on.

Five weeks from kickoff to a fundable foundations plan. The work runs in five phases with defined inputs, defined outputs, and a fixed time allocation.

Week 1

Scoping & Stakeholder Mapping

Working session with leadership, IT, and operations to lock the scope, identify data owners, and confirm the AI use cases the foundations work must support.

Week 1–2

Landscape Audit

Hands-on review of source systems, integration points, warehouses, and ad hoc spreadsheets. Documented in a single landscape map, with owners and refresh cadence captured.

Week 2–3

Quality & Readiness Scoring

Each priority dataset is scored against a consistent rubric. We sample the data, validate the score, and flag the issues that would block AI delivery.

Week 3–4

Architecture & Governance Design

We design a target-state architecture and governance framework, sized to your business and aligned to your AI roadmap. Build vs partner decisions made explicit.

Week 5

Roadmap Review & Sign-Off

Working draft reviewed with your leadership team, refined, and presented as a final document with a sixty-minute board briefing. You leave with a fundable foundations plan.

ROI focus

What it actually saves you.

Most failed AI initiatives die at the data layer. The cost of skipping foundations work is not the consulting fee; it is the eighteen-month build that never goes to production because the data underneath it cannot be trusted.

0–80%

Reduction in AI rework

Teams that fix data foundations before building agents and automations ship significantly less throwaway work. The spend is lower and the path to production is shorter.

0–3×

Faster AI delivery

Initiatives built on a clean, governed data layer move two to three times faster than those that try to fix data and ship AI at the same time.

0 weeks

From kickoff to roadmap

A fixed-scope engagement designed to produce a fundable foundations plan, not an open-ended data transformation programme.

What you walk away with

A documented map of every system that matters for AI
An honest readiness score for each priority dataset
A target-state architecture sized to your business
A governance framework aligned to Australian regulation
A sequenced roadmap your finance team can fund

Common questions

What people ask before they book.

Often, yes. A warehouse is one input, not a strategy. The Foundations engagement focuses on whether the data inside it (and outside it) is fit for AI delivery, and on the governance layer most warehouses do not provide.

Next step

Fix the data foundation before you spend on the model.

A 30-minute Strategy Session is the right starting point. We will talk through your current data landscape, the AI initiatives it needs to support, and whether a Foundations engagement is the right next step. No vendor pitch. No obligation.

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