Tertiary education
Academic and professional staff agreements, workload provisions, fixed-term rules, allowances and approval workflows.
Precision AI for regulatory compliance
Wattle AI Engine
Enterprise agreement automation that turns complex workforce rules into explainable, testable runtime logic before roster and payroll decisions become compliance risk.
- EA-first
- We implement the agreement before the first customer workshop.
- Real-time
- Roster, timesheet and payroll events checked as they happen.
- Audit-ready
- Every outcome traces back to source clauses, tests and releases.
- EA-first
- We implement the agreement before the first customer workshop.
- Real-time
- Roster, timesheet and payroll events checked as they happen.
- Audit-ready
- Every outcome traces back to source clauses, tests and releases.
Launch focus
Enterprise agreements are the first wedge.
Wattle AI is focused first on tertiary education and healthcare, where pay rules, shift penalties, leave, allowances and fatigue controls are too complex to validate after the fact.
Healthcare workforce
Public and private medical workforce agreements, with shift penalties, leave, attestation and roster-change controls.
Health tech licensing
The same engine can encode complex clinical guidelines and explainable workflow logic for partner platforms.
The operating problem
Compliance failure is usually discovered too late.
Large organisations still rely on manual interpretation, services-heavy configuration and post-payroll reconciliation for agreements that directly affect cost, compliance and workforce safety.
- Overtime and penalties can remain invisible until payroll.
- Manual implementation pushes risk onto the customer.
- Prompt-only AI cannot guarantee repeatable decisions.
- Executives need a source-linked audit trail, not just a dashboard.
How Wattle works
From agreement text to real-time operational decisions.
Wattle combines AI-assisted authoring with a deterministic runtime. The result is executable content that can be tested, versioned, audited and deployed at low compute cost.
Regulation
Enterprise agreement, award, guideline or policy source
01
AI authoring
Agentic workflows convert raw clauses, definitions and tables into Wattle assets.
02
Domain models
Typed structures define shifts, employees, leave, penalties, roles and events.
03
Logic and algorithms
WattleScript expresses rate tables, penalties, temporal checks and optimisation rules.
04
Wattle Engine
Deterministic execution collects outputs, explanations, timers and audit records.
Outputs
Roster optimisation, payroll warnings, attestation and reports
Why not prompt-only AI?
Generative AI helps author the rules. It should not be the runtime.
| Requirement | Prompt-only generative AI | Wattle AI Engine |
|---|---|---|
| Repeatable decisions | Same prompt and context can still produce different outputs. | Same inputs produce the same verified outputs. |
| Hallucination control | Outputs can vary with model, prompt and context length. | Runtime logic is typed, checked and deterministic. |
| Explainability | Generated explanations are hard to validate at scale. | Outputs link to source clauses, logic, tests and release history. |
| Production cost | High compute cost for every operational decision. | Low-cost runtime designed for high-volume event processing. |
| Governance | Prompts and guardrails need rework as models change. | Versioning, quality gates, monitoring and audit are built in. |
Customer approach
We reduce implementation risk before procurement starts.
Wattle AI can implement the target agreement before the first formal customer meeting. That changes the conversation from services risk to evidence: the customer can see their own rules running against realistic roster, timesheet and payroll scenarios.
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01
Agreement intake
Provide the agreement, award, policy material and representative data shape.
-
02
Executable implementation
Wattle converts clauses, definitions and tables into domain models and WattleScript.
-
03
Live evidence
Demonstrate compliance checks, optimisation opportunities and audit trails before rollout.
Built for governed automation
A full engine for rules that affect pay, compliance and safety.
Static checking
Strongly typed domain models and logic checks catch errors before deployment.
Provenance
Source clauses, generated code, tests and runtime outputs stay linked.
Quality gates
Testing, release management and versioning are part of the authoring lifecycle.
Low-latency runtime
Bytecode and Rust execution support real-time roster and payroll events.
Data quality
Incoming data can be mapped, validated, warned or rejected before decisions run.
Operational outputs
Warnings, tags, calculations, timers, reports and APIs feed the systems already in use.
General engine
The same capability applies to complex clinical guidelines.
Enterprise agreements are the immediate launch focus. The Wattle AI Engine is broader: it can encode clinical pathways, guideline logic, risk scoring, timers and explainable workflow automation for health tech companies that need governed decision infrastructure.
Team
Clinical AI, health technology and workforce operations experience.
Malcolm Pradhan
Founder and CEO. Clinical AI researcher, MBBS and PhD, and co-founder of Alcidion Group.
Thomas Glanville
GM Customer Solutions. Health management consultant across analytics, transformation and funding.
John Meckiff
GM Commercial. Consulting and operational leadership across healthcare and labour optimisation.
Request a demo
Bring us an agreement.
Send us an enterprise agreement, award, clinical guideline or policy. A public link is enough to start — if it is complex enough that services teams usually become the risk, it is the right test for Wattle AI.
We will assess the content and, in most cases, implement part of it so you can see your own rules running before we meet.