As Australia builds as much as the federal election, debates round sovereignty, nationwide safety, and financial resilience are taking centre stage.
Concurrently, the startup ecosystem is awash with vibe-coded client apps.
However coding with Lovable is simply the beginning of a deeper shift: the AI alternative on this decade gained’t simply be in frontend instruments.
Will probably be in rebuilding infrastructure, safety, and interoperability for an AI-native, fragmented world.
Listed here are 10 startup concepts I’d like to see bold Australian founders deal with, from sovereign GPU clouds to zero-knowledge inference layers, anchored in three highly effective macro traits:
1. The nearshoring of vital infrastructure in a multipolar geopolitical world
2. The reimagining of interoperability and safety for mannequin context protocols (MCPs), and positioning Australia as a world chief
3. AI on the edge, in bandwidth-constrained or rugged environments
Market Pattern: The nearshoring of vital infrastructure in a multipolar geopolitical world
Nationalised GPU Cloud Stack
A sovereign, onshore GPU cloud for delicate sectors (e.g. defence, intelligence, healthcare), targeted on safety, latency, and information management.
Swarm AI for Drones
Coordinated autonomous drone swarms powered by edge AI, safe mesh networks, and nationalised inference management. These may very well be used for emergency providers, vital infrastructure or agriculture
Multi-Modal Intelligence for Important Infrastructure
AI fashions that fuse audio, imaginative and prescient, RF, satellite tv for pc, and sensor information for real-time monitoring of ports, grids, airports, vitality infrastructure or mining operations — important for management, emergency response and anti-terror surveillance
Artificial Knowledge for Regulated Sectors
Enterprise-grade artificial information engines for healthcare, finance, and so on usable for mannequin coaching with out breaching compliance. For instance an artificial digital medical document engine that mimics actual affected person trajectories for AI coaching and growth
Market Pattern: The reimagining of interoperability and safety for mannequin context protocols (MCPs), and positioning Australia as a world chief
Mulesoft for MCPs
A middleware orchestration layer that integrates throughout AWS, Azure, and GCP constructed natively for AI workflows and inference routing
Zero-Information AI Inference Layer
Allow AI inference on encrypted information utilizing zkML (zero-knowledge machine studying), supreme for finance, defence, and healthcare. Retains information non-public even throughout mannequin execution
Terraform for AI Infrastructure
Infrastructure-as-Code for orchestrating AI workflows throughout clouds and hybrid stacks.
Market Pattern: AI on the edge, in bandwidth-constrained or rugged environments
Low-Vitality Mannequin Inference Chips
Startup-grade alternate options to NVIDIA, targeted on ultra-low-power inference for cellular, wearables, or edge IoT
Reminiscence-Conscious Native Brokers
Edge brokers with embedded short- and long-term reminiscence modules, to allow them to adapt and enhance regionally over time with no cloud ‘roundtrip’
Hardened LLMs for Arduous Circumstances Use
Create fine-tuned LLMs with embedded situational consciousness and edge survivability. These can be tailor-made for excessive circumstances and vary; with minimal web dependency, compressed weights, and offline reasoning capabilities
Have an AI concept that would form Australia’s future? Apply now for Antler’s August 2025 residency in Sydney, Melbourne, and Brisbane and switch your imaginative and prescient into influence.
* James McClure is a Associate at Antler Australia
