Which firms is Cassandra's AI consulting suited to?

Accounting practices, law firms, corporate tax and legal teams, and other professional-services firms in Australia that need AI outputs to be accurate, citable and reviewable. Engagements range from solo practitioners to mid-tier and national firms.

Do you build custom systems or implement existing tools?

Both. Where an existing tool fits, we integrate it into your workflows. Where the requirement is specific — typically retrieval over your own knowledge base — we design and build it, usually on the same architecture that runs Cassandra's own engines.

How is professional-obligation risk handled?

Up front. Each engagement starts by mapping the relevant obligations — TPB Code of Professional Conduct, APES 110, the Legal Profession Uniform Law and the Privacy Act 1988 — and designing review gates, logging and accountability to satisfy them before any system is built.

Where is client data processed?

In Australian cloud regions by default, encrypted in transit and at rest. Cross-border processing is only used where a firm explicitly chooses it.

How long does a typical engagement take?

A scoped opportunity assessment runs two to four weeks. A retrieval or integration build typically runs eight to sixteen weeks depending on the corpus and the systems involved. Governance frameworks are usually delivered alongside a build rather than as a standalone project.

Book a call. We'll discuss the workflow you want to change, what systems it touches and what a defensible outcome looks like, then propose a fixed scope.

AI Consulting Australia | Professional Services

What Cassandra's Consulting Practice Does

Most AI consulting sold to Australian firms is generic: a strategy deck, a chatbot pilot, and a governance template that never touches a live matter. Cassandra's consulting practice is different because it grew out of building a production research engine for Australian tax and legal work — the same retrieval, citation and review problems every professional firm faces.

Engagements typically cover one of three things: designing and building retrieval-augmented (RAG) systems over a firm's own precedents and knowledge base; evaluating and integrating LLM tooling into existing practice-management workflows; or establishing AI governance that satisfies professional obligations under the TPB Code of Professional Conduct, APES 110 and the Legal Profession Uniform Law.

Every engagement ends with something running in your environment, with the review controls a partner can sign off on.

The Problems Professionals Face

Managing Partner

Pressure to 'do something with AI' without a clear view of risk, cost or where it actually saves time

→ A scoped opportunity assessment tied to specific workflows, with the professional-obligation analysis done up front

Practice Manager

Vendor tools that don't integrate with the firm's document system, email or practice management software

→ Integration design and build against your actual stack — Microsoft 365, Xero, iManage, LEAP, APS and similar

Knowledge Manager

Years of precedents and prior advice that nobody can search reliably

→ A retrieval system over your own corpus with citations back to the source document and paragraph

Risk & Compliance

No documented position on how AI outputs are reviewed before they reach a client

→ An AI governance framework with review gates, logging and accountability mapped to your professional standards

Key Capabilities

RAG & Knowledge Systems

Retrieval-augmented generation over firm precedents, prior advice, and primary sources, with paragraph-level citations

LLM Integration

Evaluate, select and integrate language-model tooling into existing document, email and matter workflows

Document Intelligence

Extraction, classification and summarisation pipelines for contracts, financial statements and regulatory filings

AI Governance

Review gates, audit logging and accountability structures aligned with TPB, APESB and Legal Profession Uniform Law obligations

Data Residency & Security

Architectures that keep client data in Australian regions with encryption in transit and at rest

Adoption & Training

Role-specific training so juniors, seniors and partners each know what to trust, what to check, and what to reject

Why Generic AI Consultancies Struggle With Professional Firms

They have not built systems where a wrong citation is a professional-conduct issue, so review controls are an afterthought
They treat Australian legislation like any other document set, missing the structure of the ITAA, ATO guidance hierarchy and court precedent
They pilot chatbots rather than integrating with the document and matter systems where the work actually happens
They cannot speak to TPB, APES 110 or Uniform Law obligations when a partner asks whether the design is defensible

Why Firms Engage Cassandra

We run a production tax and legal research engine on Australian primary sources — the consulting practice applies what that taught us
Engineers and qualified practitioners work on the same engagement, so architecture and professional obligations are designed together
Every build ships with source citations and review gates rather than unverifiable outputs
Australian-registered company (ABN 70 659 258 367) with Australian data residency by default
Fixed-scope engagements with a working system as the deliverable, not a recommendation deck