A VC’s list of 10 startup ideas Australian founders should tackle

As Australia builds up to the federal election, debates around sovereignty, national security, and economic resilience are taking centre stage.

Concurrently, the startup ecosystem is awash with vibe-coded consumer apps. 

But coding with Lovable is just the start of a deeper shift: the AI opportunity in this decade won’t just be in frontend tools.

It will be in rebuilding infrastructure, security, and interoperability for an AI-native, fragmented world. 

Here are 10 startup ideas I’d love to see ambitious Australian founders tackle, from sovereign GPU clouds to zero-knowledge inference layers, anchored in three powerful macro trends:

1. The nearshoring of critical infrastructure in a multipolar geopolitical world

2. The reimagining of interoperability and security for model context protocols (MCPs), and positioning Australia as a global leader

3. AI at the edge, in bandwidth-constrained or rugged environments

Market Trend: The nearshoring of critical infrastructure in a multipolar geopolitical world 

Nationalised GPU Cloud Stack 

A sovereign, onshore GPU cloud for sensitive sectors (e.g. defence, intelligence, healthcare), focused on security, latency, and data control. 

Swarm AI for Drones 

Coordinated autonomous drone swarms powered by edge AI, secure mesh networks, and nationalised inference control. These could be used for emergency services, critical infrastructure or agriculture 

Multi-Modal Intelligence for Critical Infrastructure 

AI models that fuse audio, vision, RF, satellite, and sensor data for real-time monitoring of ports, grids, airports, energy infrastructure or mining operations — vital for control, emergency response and anti-terror surveillance 

Synthetic Data for Regulated Sectors 

Enterprise-grade synthetic data engines for healthcare, finance, etc usable for model training without breaching compliance. For example a synthetic electronic medical record engine that mimics real patient trajectories for AI training and development

Market Trend: The reimagining of interoperability and security for model context protocols (MCPs), and positioning Australia as a global leader 

Mulesoft for MCPs 

A middleware orchestration layer that integrates across AWS, Azure, and GCP built natively for AI workflows and inference routing 

Zero-Knowledge AI Inference Layer 

Enable AI inference on encrypted data using zkML (zero-knowledge machine learning), ideal for finance, defence, and healthcare. Keeps data private even during model execution 

Terraform for AI Infrastructure 

Infrastructure-as-Code for orchestrating AI workflows across clouds and hybrid stacks. 

Market Trend: AI at the edge, in bandwidth-constrained or rugged environments 

Low-Energy Model Inference Chips 

Startup-grade alternatives to NVIDIA, focused on ultra-low-power inference for mobile, wearables, or edge IoT 

Memory-Aware Local Agents 

Edge agents with embedded short- and long-term memory modules, so they can adapt and improve locally over time with no cloud ‘roundtrip’ 

Hardened LLMs for Arduous Conditions Use 

Create fine-tuned LLMs with embedded situational awareness and edge survivability. These would be tailored for extreme conditions and range; with minimal internet dependency, compressed weights, and offline reasoning capabilities 

Have an AI idea that could shape Australia’s future? Apply now for Antler’s August 2025 residency in Sydney, Melbourne, and Brisbane and turn your vision into impact. 

 * James McClure is a Partner at Antler Australia