Sovereign AI Solutions for Every Scale
From secure, high-performance inference to custom model fine-tuning, our platform provides the building blocks for enterprise-grade AI, all hosted within Australian legal jurisdiction.
Platform Capabilities
Scalable Inference
Access dozens of open-source and custom models on high-performance infrastructure with pay-as-you-go pricing.
Model Fine-Tuning
Adapt models to your specific domain with our managed fine-tuning service or bring your own environment.
Developer-Ready API
Integrate AI into your applications in minutes with our OpenAI-compatible REST API and SDKs.
Sovereign & Secure
Ensure data residency and compliance with our platform, hosted exclusively in Australian data centers.
Industry-Specific Use Cases
SouthernCrossAI delivers real-world value across finance, government, enterprise, and AI-native builders—using sovereign-hosted AI models tuned for Australian needs.
Financial Services
Smarter, faster fiduciary services—compliant by design.
Business Problems
- ▪Document-heavy trust operations slow onboarding and audit.
- ▪ESG compliance is fragmented across disclosures and sources.
- ▪Personalised client insights require costly adviser time.
AI Solutions
- ▪TrustDoc AI Reviewer: Parses deeds, flags inconsistencies.
- ▪ESG Scan Engine: Screens ASX filings for sustainability risks.
- ▪AI Wealth Assistant: Personalised GPT-style adviser.
Token Economics
- ▪TrustDoc: ~25M tokens/year per business unit.
- ▪ESG Scan: ~10M tokens/month for full coverage.
- ▪Adviser Assistant: ~10K–30K tokens/client/month.
Government & Public Sector
Secure, sovereign AI for enhanced public service delivery.
Business Problems
- ▪Document workflows require redaction, summarisation, validation.
- ▪Fraud risk in forms and grants is hard to detect at scale.
- ▪Public data must not leave Australian legal jurisdiction.
AI Solutions
- ▪Document AI Processor: Scans and indexes public submissions, FOIs, and regulatory forms.
- ▪FraudShield: Detects anomalies in grant or benefits applications using few-shot examples.
- ▪Sovereign Citizen Bot: Provides 24/7 automated support for citizen inquiries, with all data processed onshore.
Token Economics
- ▪Doc Processor: ~50K tokens per 100-page report.
- ▪FraudShield: ~1M tokens per 10,000 applications.
- ▪Citizen Bot: ~5M tokens/month per 100K inquiries.
Enterprise & Corporate
Unlock productivity and mitigate risk with secure AI.
Business Problems
- ▪Internal knowledge is siloed in documents and wikis.
- ▪Customer support teams are overwhelmed by repetitive queries.
- ▪Legal contract review is a manual bottleneck.
AI Solutions
- ▪Enterprise RAG Chatbot: Secure Q&A over internal data, wikis, and document stores.
- ▪AI Support Agent: Automates responses to common tickets and escalates complex issues.
- ▪Legal Clause Analyser: Flags risks, deviations, and obligations in legal contracts.
Token Economics
- ▪Enterprise RAG: ~20M tokens/month for 1,000 users.
- ▪AI Support Agent: ~2K tokens per resolved ticket.
- ▪Legal Analyser: ~100K tokens per contract.
AI Builders & ML Teams
Access powerful GPU infrastructure and model services for training and deployment.
Business Problems
- ▪GPU infrastructure is expensive and complex to manage.
- ▪Training custom models requires significant compute resources.
- ▪Scaling inference workloads while maintaining cost efficiency.
AI Solutions
- ▪GPU-as-a-Service: On-demand or reserved GPU clusters with transparent pricing.
- ▪Managed Fine-Tuning: Expert support for tuning models on proprietary data.
- ▪Scalable Inference Endpoints: Production-ready endpoints with predictable performance.
- ▪Sovereign GPU Racks: Access to high-density inference or BYO fine-tuning environments in Sydney or Whyalla.
Token Economics
- ▪GPU rentals billed per hour with options from A$3.00/hour.
- ▪Fine-tuning as a managed service fee.
- ▪Inference billed per million tokens.
- ▪Reserved Pods offer up to 60% cost savings compared to on-demand pricing.
Healthcare & Life Sciences
Accelerate discovery and improve patient outcomes with AI.
Business Problems
- ▪Clinical notes are unstructured and difficult to analyse.
- ▪Accessing relevant medical research is time-consuming.
- ▪Clinical trial data extraction is manual and error-prone.
AI Solutions
- ▪AI-powered clinical note summarisation and entity extraction.
- ▪RAG over a corpus of medical research papers and trial results.
- ▪Automated data extraction from clinical trial documentation.
Token Economics
- ▪Note summarisation: ~10K tokens per 1-hour appointment.
- ▪QA over medical corpus: ~2M–5M tokens/month.
- ▪Trial data extraction: ~15M tokens per research cycle.