Fair Work Case Law Database: 2,300+ Live FWC & Federal Court Decisions

Looking for the official Fair Work Commission decisions database, or AustLII's archive? See where to search FWC decisions — it compares the three sources with direct links. This article is about why a live, summarised corpus beats a general-purpose AI model.

Ask a general-purpose AI assistant "how much notice does an Australian employer have to give for redundancy?" and you'll get a confident answer. Some of it will be right. Some will reference outdated NES tables, an obsolete cap, or US notice-period concepts that don't exist here. The model has no idea which is which — its training data ended a year or more ago, and it doesn't know what the Fair Work Commission decided yesterday, last week or last quarter.

That's not a flaw in the model. It's the fundamental limit of how frontier LLMs work. They're trained on a snapshot of the internet, sealed at some past date, and they can't reach out to Australia's Fair Work Commission, Federal Court, or Fair Work Ombudsman to check what's actually decided.

For an Australian HR team running a real workplace, that gap matters. Cases get decided weekly. Awards change. Penalties get awarded. The decision that came down on Friday — the one that changes how your case-in-question will be weighed — is not in any frontier LLM's knowledge.

FairWork Mate runs a live database of Australian workplace decisions. As of September 2026, that's 2,300+ decisions across three jurisdictions, all browsable at /cases:

• Fair Work Commission (FWC) — the federal tribunal hearing unfair dismissal, general protections, bargaining, anti-bullying and modern award matters. Thousands of decisions a year; we're publishing the substantive ones with plain-English summaries.
• Federal Court of Australia (FCA) — the higher court hearing Fair Work civil-penalty proceedings, sham contracting prosecutions, larger appeals. Where the real precedent gets set.
• Fair Work Ombudsman (FWO) — enforcement outcomes, enforceable undertakings, litigation against employers. More than 2,000 enforcement outcomes in the corpus, from $1M+ restaurant prosecutions to $20M university settlements.

Each case is summarised into facts, outcome, employer implication and employee implication. Each one has tags, an industry classification, a penalty figure where applicable, and a permanent URL. Each one is also embedded as a high-dimensional vector — which means our AI advisor can find the most relevant 2-3 cases to your question in milliseconds and cite them directly in the answer.

Ask FairWork Mate AI "is performance management of a pregnant employee at risk under general protections?" and the answer doesn't just give you the legal framework — it cites specific FWC and FCA decisions with the actual reasoning the bench applied, so you can read the source yourself.

Q1: "Can my employer reduce my pay below the award without my consent?"

• FairWork Mate AI: Cites the modern award floor, references s 323 of the Fair Work Act, names relevant FWC decisions on unilateral pay reductions, and links to the case-page summaries.

Q2: "We have a casual who's worked the same Tuesday-Thursday shifts for 14 months. Are we exposed?"

• FairWork Mate AI: Explains the employee choice pathway introduced by the 2024 Closing Loopholes reforms (a casual can notify after 6 months of employment, or 12 months with a small business employer), the "regular and systematic" factors in the casual definition, relevant FWC decisions, and links to the FairWork Mate casual conversion calculator.

Q3: "What's the precedent for $50k+ general protections compensation in 2025?"

• FairWork Mate AI: Names recent Federal Court decisions from the corpus with the compensation awarded, the reasoning, and the relevant industry context. Citations and links included.

The common thread: a model answering only from its training data can't reliably point to a decision handed down after its cutoff. Retrieval from a current case database can.

Every case we publish makes the next answer better. The AI retrieval is similarity-based, so a question about retail wage theft pulls the most-similar retail wage-theft cases automatically. The corpus growing from a few hundred decisions in early 2026 to more than 2,300 today doesn't just give us more pages — it gives the AI a denser retrieval space, more specific citations, and more accurate edge-case reasoning.

Frontier LLM training is competitive but bounded. The next generation of general-purpose models will still have a training cutoff date and still won't know about Tuesday's FWC decision. The moat for Australian workplace law isn't bigger models. It's live, jurisdiction-specific, plain-English-summarised case data, retrieval-attached to the AI. That's what we're building.

The corpus passed 1,000 published Australian workplace decisions in mid-2026 and now exceeds 2,300, with nightly refresh, full embeddings, and an AI advisor you can try free at /advisor. For HR teams running real estates of workers and contracts, that's already the most useful Australian workplace AI tool on the market. If you're used to generic answers to specific Australian questions, it's worth a 5-minute trial.

If you run people in Australia, three concrete uses:

• Case-law research without the lawyer-billable hour. The "what's the precedent for X" question used to mean an hour of legal research at $400-700/hr. Now it's a 30-second AI advisor query with cited decisions. Validate it with your lawyer if it's high-stakes; skip the lawyer's research time if it's not.
• Drafting compliant documents grounded in current law. Show-cause letters, casual conversion responses, performance plans — drafted by our AI with the relevant statutory references and recent case law cited in the same answer.
• Industry-specific intelligence. What's happening in aged-care underpayment in 2026? Which universities have signed enforceable undertakings over casual academic pay? What's the FCA awarding for unfair dismissal in finance? Searchable by industry and tag.

For solo HR managers, small-business owners and operators, /advisor is free to try. For teams running multiple workflows, the For Business tiers give bigger question pools, longer context and team seats.

The data is the moat. The AI on top of it is the interface. Both are live now. The only AU workplace AI source citing 2,300+ live decisions is FairWork Mate. The number's growing nightly.