SHARON AI, Australia’s leading Neocloud, has announced that it has partnered with VAST Data, the AI Operating System company, to serve enterprise and government customers with inference at any scale.
The VAST InsightEngine is an end-to-end ingestion, embedding, indexing and retrieval system that lets organisations continuously ingest structured, unstructured and streaming data in real time – feeding inference systems by delivering low-latency, massively parallel vector and hybrid search for RAG and agentic workflows at scale. Integrated within the VAST AI OS, it inherits unified governance, security, and lineage, enforcing policy-based access controls, encryption and auditability across every query.
“As AI systems grow more capable, the ability to reason securely over large datasets in real time will define the next generation of enterprise intelligence,” said Ofir Zan, AI Solutions & Enterprise Lead, VAST Data. “Together, SHARON AI and the VAST InsightEngine orchestrate event triggers and functions connected to data pipelines that scale complex multistep retrieval and reasoning workflows — all within a sovereign environment.”
By uniting these technologies, SHARON AI moves organisations from experimentation to production with repeatable, enterprise-grade workflows. In financial services, where high throughput and low latency inference are essential, it powers RAG at any scale using a large native vector index to search through billions of embedded records, while enforcing fine-grained permissions.
In public safety and smart cities, ingesting massive volumes of video and metadata while processing and analysing them in real time cuts operational costs, improves situational awareness and incident response, and is done while keeping sensitive data within borders.
“By combining SHARON AI’s sovereign GPU cloud with the VAST InsightEngine we’re creating the foundation for enterprises and government institutions to run cutting-edge AI workloads locally, securely, and without compromise,” said Wolf Schubert, CEO of SHARON AI. “With our supercluster now live in NEXTDC’s Tier IV M3 data centre in Melbourne, this milestone demonstrates our commitment to delivering sovereign, high-performance AI infrastructure for Australia.”
The first workloads on the cluster are underway with University of New South Wales (UNSW) researchers collaborating with SHARON AI cloud to advance reasoning-focused AI research across multiple domains. PhD students are using these resources to:
- Improve reasoning in small language models through structured reasoning, auto formalisation, and novel expert-aware post-tuning of Mixture-of-Experts architectures.
- Fine-tune and evaluate state-of-the-art LLMs (Falcon, Llama, Qwen, Deepseek, etc.) in parallel for tasks such as QA, with applications to math and spatio-temporal reasoning.
- Accelerate global weather forecasting, training high-resolution data-driven models on large-scale ERA5 datasets for faster and more accurate prediction.
Collectively, the work explores how specialised post-tuning, fine-tuning, and GPU-accelerated model architectures can enhance reasoning performance, scalability, and domain-specific applications of AI. This effort by UNSW researchers is laying the groundwork for smaller, more efficient, and more capable reasoning models that can be applied across science, forecasting, and advanced AI evaluation.
