Research Showcase

Real-world applications of autonomous agent architectures in Australian regulatory compliance, critical infrastructure protection, and legal technology. All research conducted under Australian Privacy Principles and OSINT Foundation ethical standards.

Study 1: Entity Resolution in Complex Australian Corporate Structures

Corporate Intelligence

Abstract

We investigated whether autonomous agents could identify concealed relationships between ostensibly independent entities within Australian corporate networks. Deploying 472 specialized agents across ASIC registries, shareholder records, director identification databases, and ASX disclosures, we applied probabilistic entity resolution to correlate name variations across ABN/ACN records.

Approach

472 specialized agents deployed across regulatory databases
Probabilistic entity resolution across ASIC registries
Network analysis of shareholder and director relationships
Correlation of name variations in ABN/ACN records

Outcome

Network analysis revealed that two apparently unrelated entities shared beneficial ownership through a complex web of intermediary companies, demonstrating the effectiveness of multi-agent systems in uncovering concealed corporate relationships.

Applications

This methodology has applications for AUSTRAC compliance, foreign investment review board (FIRB) assessments, and ASX continuous disclosure verification.

Study 2: Autonomous Alert Correlation in Critical Infrastructure Security

Critical Infrastructure

Abstract

We examined the feasibility of agent-based triage within Australian critical infrastructure security operations. An experimental swarm architecture ("MCP-β") was deployed in an energy-sector SOC designated under the Security of Critical Infrastructure Act 2018. The system processed 70,000 daily alerts through autonomous clustering, ASD threat indicator correlation, and ACSC threat intelligence integration.

Approach

Swarm architecture deployment in energy-sector SOC
Processing 70,000 daily security alerts
Autonomous clustering and correlation algorithms
Integration with ASD and ACSC threat intelligence

Outcome

Over 30 days, median time-to-verify decreased from 4h34m to 46m, with analyst workload reduced by 73% while maintaining 99.2% accuracy in threat classification.

Ongoing Challenges

Legacy SCADA systems in Australian infrastructure present unique obstacles, particularly those using obsolete encoding standards in industrial historians.

Study 3: Geospatial Verification in Australian Legal Proceedings

Legal Technology

Abstract

This study explored multi-modal analysis for location verification in the context of Australian civil litigation, where traditional digital evidence was unavailable. Vision-enabled agents analyzed publicly available imagery for distinctive Australian geographical features (water infrastructure, native vegetation patterns). Specialized agents performed EXIF data recovery and flora-based temporal analysis specific to Australian seasonal patterns.

Approach

Multi-modal analysis of publicly available imagery
Recognition of distinctive Australian geographical features
EXIF data recovery and metadata analysis
Flora-based temporal analysis using Australian seasonal patterns

Outcome

Target location verified and temporal consistency established within acceptable legal standards, demonstrating the viability of AI-assisted evidence verification in Australian legal contexts.

Applications

The approach demonstrates potential applications for emergency services location verification and environmental compliance monitoring under EPBC Act requirements.

Methodological Framework

Our research employs a distributed agent architecture comprising 500+ task-specific models trained on Australian regulatory and commercial datasets. All findings include complete provenance documentation meeting Australian rules of evidence standards. Code and documentation available via public repository under appropriate licenses.

Ethical Considerations

All research conducted under Australian Privacy Principles (APP), Office of the Australian Information Commissioner (OAIC) guidelines, and OSINT Foundation ethical standards. Data collection complies with Privacy Act 1988 (Cth) requirements. Examples utilize public domain data or appropriately de-identified datasets.

Research Collaboration

We welcome proposals for collaborative research, particularly those addressing challenges in Australian regulatory compliance, critical infrastructure protection, or legal technology applications.

Correspondence: research@oselab.ai