SCX.ai Partners With DDN to Scale Australian Sovereign AI Inference Infrastructure

Australian sovereign AI infrastructure provider SCX.ai has entered a strategic partnership with data storage systems vendor DDN to expand its domestic AI inferencing cloud. The collaboration combines SCX's ASIC-based compute clusters with DDN's Infinia data management platform, targeting enterprise, government, and scientific research workloads that must remain strictly within Australian jurisdiction. The agreement comes days after SCX completed a $40 million initial public offering on the Aust

2 min
SCX.ai Partners With DDN to Scale Australian Sovereign AI Inference Infrastructure

Australian sovereign AI infrastructure provider SCX.ai has entered a strategic partnership with data storage systems vendor DDN to expand its domestic AI inferencing cloud. The collaboration combines SCX's ASIC-based compute clusters with DDN's Infinia data management platform, targeting enterprise, government, and scientific research workloads that must remain strictly within Australian jurisdiction.

The agreement comes days after SCX completed a $40 million initial public offering on the Australian Securities Exchange (ASX: SCX) on August 21, 2026. The funds are earmarked for deploying multi-node inference clusters across domestic data centers.

ASIC processor architecture and high-throughput KV cache memory storage tiering

ASIC Silicon and I/O Acceleration

SCX builds its inferencing infrastructure on SambaNova SN40L AI processors rather than conventional GPU clusters. The systems use air cooling instead of water-intensive liquid loops, designed to fit standard enterprise data center power envelopes without requiring facility retrofits. Testing disclosed by SCX prior to its ASX listing indicated that the SambaNova architecture achieves between 2.5x and 5.6x higher performance per watt compared to GPU-based alternatives across selected inference workloads.

DDN is integrating its Infinia platform into the compute architecture to address I/O serialization during large-scale inference. According to DDN, the software-defined data platform delivers sub-millisecond access latency and up to 27-fold faster key-value (KV) cache loading times. Accelerating KV cache retrieval is critical for multi-turn agentic workflows and long-context processing, where transferring large context states between storage and memory creates execution bottlenecks.

Sovereign Deployment Footprint and Commercial Traction

The deployment aims to address data residency and extraterritorial compliance challenges under foreign statutes such as the US CLOUD Act, which can subject US-headquartered cloud providers to foreign data access requests even when hardware is physically located in Australia.

SCX reported $6.5 million in contracted annual recurring revenue at the end of July 2026, marking a 20.9% increase from May, with more than 400 active platform users. The company operates its initial production node at the Equinix SY5 data center in Sydney. It plans to bring a second node online by late 2026, while expanding its infrastructure to host Project MAGPiE, a sovereign foundation language model adapted for Australian public-sector and enterprise environments.

Sources

Written by

More to read

  • Robotics Foundation Model Startup Generalist Raises 98M Led by 8VC

    Robotics foundation model startup Generalist AI Inc. has secured $198.2 million in a new equity offering, according to a Form D regulatory filing with the U.S. Securities and Exchange Commission on August 24. The capital injection comes less than three months after the company closed a $400 million financing round in early June. The financing round was led by venture capital firm 8VC alongside participating existing investors, as reported by Axios. The new transaction elevates Generalist's valu

    1 min
  • Chinese State-Linked Hackers Double Attack Volume Using DeepSeek AI, Researchers Find

    State-affiliated Chinese cyber espionage groups have more than doubled their operational attack volume by integrating open-weight artificial intelligence models into routine reconnaissance and script generation workflows, according to threat intelligence from Taiwanese cybersecurity firm TeamT5 and reporting by Bloomberg. The surge in offensive volume is driven primarily by DeepSeek models, which threat actors favor due to low inference costs, local deployment options, and minimal safety guardr

    1 min
  • Adversarial Jailbreak Defenses in Production LLMs: Input Perturbation, Representation Circuit Breakers, and Guardrail Cascades

    Standard post-training alignment techniques such as Supervised Fine-Tuning (SFT) and Direct Preference Optimization (DPO) instill safety constraints into large language models by shaping token probabilities toward refusal strings. In production environments, however, these surface-level behavioral alignments have proven brittle against systematic adversarial inputs. Gradient-driven token optimization methods such as Greedy Coordinate Gradient (Zou et al., 2023), automated genetic search algorith

    1 min