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Data Factorial

Data, AI, and Technology Advisory for Australian Businesses

Make your business data safe, governed, and ready for AI.

Data Factorial helps Australian businesses identify sensitive data exposure, improve governance, reduce vendor and AI risk, and turn fragmented data into a trusted business asset.

Before you roll out AI, automation, analytics, or more SaaS tools, you need confidence that your data is visible, protected, governed, and safe to use.

Data & AI confidence

Signals we clarify

Structured visibility across exposure, control, vendors, AI use, and reporting — without claiming automated scoring.

Sensitive data visibility

Critical data, flows, and storage locations understood.

Access control confidence

Permissions and ownership aligned to business risk.

Vendor exposure

SaaS and supplier touchpoints mapped to sensitive data.

AI readiness

Guardrails and data fitness for intended AI use.

Executive reporting

Clear artefacts boards and ELT can act on.

The gap

AI is moving faster than most data governance models.

Many businesses are adopting AI, SaaS platforms, automation, and analytics without a clear view of where sensitive data lives, who can access it, or which vendors and tools are exposed to it.

What we see in market

The mismatch between adoption speed and governance clarity shows up in predictable ways.

  • Staff may already be using AI tools with business or client data.
  • Sensitive information may be spread across SaaS platforms, shared drives, email, and cloud systems.
  • Access controls may not reflect actual business risk.
  • Customer due diligence and board questions are becoming harder to answer.
  • Data ownership and quality issues can block AI adoption.

When to engage

You may need a data and AI risk review if...

  • You are rolling out Microsoft Copilot, ChatGPT Enterprise, AI agents, or workflow automation.

  • A customer, board, investor, insurer, or auditor is asking harder questions.

  • You do not know where all sensitive data is stored or shared.

  • You rely on many SaaS vendors but lack a clear data exposure view.

  • Your leadership team needs a practical 90-day roadmap, not a generic maturity report.

Who we serve

Built for Australian businesses handling sensitive data.

We work with leadership teams that need practical clarity across data, AI, technology risk, vendor exposure, and executive decision-making.

SaaS companies selling to enterprise

Sell upstream with confidence: clarify how customer and operational data is governed before procurement and security scrutiny intensifies.

  • Customer due diligence and enterprise procurement cycles
  • Trust and assurance questions from larger buyers
  • Need a controlled narrative backed by how data is actually handled

Fintech, payments, lending, and financial services-adjacent businesses

Balance innovation with defensible data governance, resilience expectations, and AI adoption in sensitive financial workflows.

  • Material data across transactions, identity, and operations
  • Vendor and subprocessor chains that need explicit oversight
  • Board and regulator-backed expectations on resilience and conduct

Professional services firms

Protect sensitive client material across documents, email, collaboration tools, and emerging AI workflows — without slowing legitimate delivery.

  • Client confidentiality spanning many systems and channels
  • Partner and matter-level accountability for data handling
  • AI experimentation without clear enterprise guardrails

Health, care, education, and training providers

Modernise service delivery while protecting personal and sensitive information across clinical, operational, and learning environments.

  • Personal and sensitive information in longitudinal records
  • Mixed legacy and cloud environments
  • Pressure to adopt AI and automation with duty-of-care expectations

Offers

Practical advisory offers with clear executive outputs.

Data & AI Risk Discovery Workshop

A structured leadership session to align on sensitive data, AI use, vendor exposure, and what “safe and governed” means for your business.

Typical outcome: Shared priorities and a clear view of what to validate next before deeper assessment work.

Flagship offer

AI & Sensitive Data Risk Assessment

A focused assessment of sensitive data exposure, governance gaps, vendor touchpoints, and AI readiness — with executive-ready outputs.

Typical outcome: A prioritised view of risk and a practical path to improve confidence before AI scales.

Enterprise Customer Trust Readiness Review

Prepare for enterprise procurement, security questionnaires, and customer diligence with evidence-backed clarity on data handling and controls.

Typical outcome: Clearer answers under customer and partner scrutiny without improvising in the sales cycle.

Vendor & SaaS Data Exposure Review

Map where SaaS and vendor relationships intersect sensitive data, access, and subprocessors — and where blind spots create exposure.

Typical outcome: A consolidated vendor touchpoint view leadership can govern and track over time.

Fractional Data & Technology Risk Advisor

Ongoing executive advisory to steer data governance, AI guardrails, vendor decisions, and risk reporting between major projects.

Typical outcome: Consistent decision support so data and AI risk does not drift between initiatives.

View Assessment Packages

Compare scopes and outputs across workshops, assessments, and ongoing advisory.

Methodology

A structured framework for data and AI confidence.

The D.A.T.A. Confidence Framework helps leadership teams discover, assess, transform, and assure their data and AI readiness.

  1. Discover

    Identify critical data, systems, vendors, AI usage, stakeholders, and business goals.

    Focus areas

    • Critical data, systems, and vendors
    • AI usage and stakeholders
    • Business goals and engagement scope
  2. Assess

    Evaluate sensitive data exposure, governance maturity, access controls, architecture, vendor risk, and AI readiness.

    Focus areas

    • Sensitive data exposure and governance maturity
    • Access controls and architecture
    • Vendor risk and AI readiness
  3. Transform

    Build the roadmap, control uplift, governance model, data ownership model, architecture improvements, and operating cadence.

    Focus areas

    • Roadmap and governance model
    • Ownership structure and control uplift
    • Practical 90-day plan
  4. Assure

    Track progress, provide executive reporting, support board visibility, and maintain governance over time.

    Focus areas

    • Progress tracking and executive reporting
    • Governance cadence
    • Confidence over time

See how each phase is scoped, what gets handed over, and how it fits board and technical audiences.

Deliverables

Clear outputs your leadership team can act on.

Deliverables vary by scope — the aim is always artefacts executives can use for decisions, not shelf-ware.

Executive risk summary

Data and AI readiness scorecard

Sensitive data exposure map

Vendor data exposure register

Governance gap analysis

Top 10 risk register

90-day remediation roadmap

Board or ELT decision pack

Experience

Senior advisory experience across data, AI, cloud, SaaS, cybersecurity, and regulated environments.

Data Factorial connects data risk, technology decisions, AI readiness, and commercial outcomes in language leadership teams can act on.

Executive-level technology and data advisory

Support for decisions that sit at the intersection of data, AI, platforms, and accountability.

Practical architecture, governance, and risk experience

Clear-minded assessment of how controls, vendors, and operating models actually behave — not paper policies alone.

Independent guidance above implementation delivery

Advice structured for leadership outcomes, without tying recommendations to a downstream implementation quota.

Next step

Before you expose more data to AI, know what risk you are carrying.

Start with a focused discovery call to understand whether your data is safe, governed, and ready for AI.