Fortifai Ltd Launches Nol8 AI Data Plane for Cloud Testing
FortifAI brings Nol8 AI Data Plane to market with Version 1.0 launch
FortifAI Limited (ASX: FTI) has launched Version 1.0 of its Nol8 AI Data Plane, enabling NeoCloud Providers to begin customer testing and proof-of-concept engagements for demanding Agentic AI workloads. The product is designed to deliver “the right data at wire speed” for the data-intensive demands of autonomous AI agents.
The release marks what the Company describes as the latest step in bringing its technology to market for early design partners. Notably, Version 1.0 was delivered ahead of the target set out in Nol8’s roadmap, as disclosed in FortifAI’s ASX announcement dated 16 February 2026.
According to the Company, Version 1.0 “exceeds its planned functionality,” allowing design partners and customers to begin commercial assessment immediately. For investors, the milestone signals execution discipline and a measured shift from research toward commercial evaluation.
Key points from the launch include:
- Nol8 AI Data Plane Version 1.0 is available now
- Available to select design partners for testing, with broader availability to follow
- Delivered ahead of the 16 February 2026 roadmap target
- Targets governed agentic data delivery with low latency, high throughput and low total cost of ownership (TCO)
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What the AI Data Plane is, and why it matters
For investors less familiar with AI infrastructure, the modern AI stack rests on three established layers: storage, compute (both GPU and CPU processors), and fast global networks. NeoCloud Providers, specialist cloud operators building AI-specific infrastructure, are reported to be spending billions of dollars assembling these foundations.
Nol8 positions itself as the missing fourth layer in this architecture, the AI Data Plane. Its function is to give organisations wire-speed control over the data flowing to and from AI agents.
The underlying problem is one of scale and speed. Millions of AI agents will each require a unique, real-time stream of data, individually curated and governed at wire speed. Each stream must also address compliance requirements, ensuring sensitive data is not exposed to AI workloads.
Before Nol8, these requirements were typically met through large CPU arrays combined with legacy software. According to the Company, both were built for the era of human-paced workloads, making the approach expensive and constrained in feeding GPUs at the speed and volume Agentic AI demands.
The FPGA infrastructure cost savings benchmarked by Nol8 quantify this advantage in concrete terms: a single appliance replacing over 60,000 CPUs at P99 load, at under A$50,000 per year versus A$6-7.5 million for an equivalent CPU array, a comparison that reframes the TCO argument from abstract to operational.
Nol8’s approach combines a software algorithm with industry-standard accelerated hardware. The result, the Company states, is governed agentic data delivery with the industry’s lowest latency, highest throughput and lowest TCO.
| Layer | Function | Status in stack |
|---|---|---|
| Storage | Holds the data used by AI systems | Established |
| Compute (GPU & CPU) | Processes AI workloads | Established |
| Global High-Speed Network | Moves data across locations at speed | Established |
| AI Data Plane (Nol8) | Delivers governed, curated data to each AI agent at wire speed | New fourth layer |
The value proposition for NeoClouds and enterprises
The Company frames Nol8’s capabilities around two distinct beneficiary groups, each with its own value angle:
- For NeoClouds: fewer idle GPU cycles, faster capital payback, and higher margin on existing infrastructure
- For Enterprises: fast, governed data delivery for Agentic AI workloads at a materially lower total cost of ownership
The first focus areas for Nol8 with NeoClouds and their customers span four workload categories:
- Agent-to-Agent Workloads (vertical agnostic): mediating and governing high-frequency data exchange between autonomous buyers and sellers at machine speed, with policy enforced inline
- Pre-Inference: retrieval, data preparation, classification and filtering of inbound data before it reaches the model, so the GPU receives clean, governed, model-ready data
- Post-Inference: governance, redaction and routing of model outputs as they leave the GPU, enforcing compliance on results in motion
- Inline Data Governance: applying classification and policy to sensitive data as it moves, allowing data previously held back for compliance to be safely used
Kelly Herrell, CEO, Nol8
“AI agents require specific data as their fuel. It must be curated to each agent’s needs while adhering to discrete compliance policies, at wire speed. We built the AI Data Plane to address this critical requirement, ensuring every agent gets precisely the right governed data at millisecond speed and at a lower cost than alternative approaches. Through this unique combination of capabilities, Nol8 is designed to increase GPU utilisation and speed agentic actions, benefiting both NeoClouds and Enterprises.”
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What’s next for FortifAI and the investment case
Nol8 Version 1.0 is available now to select design partners for testing, with broader availability to follow. Design partners and customers can begin commercial assessment immediately, and the Company directed interested parties to lp.nol8.io.
For investors, the ahead-of-schedule delivery offers a measure of validation around execution. Moving from peer-reviewed research toward early commercial engagement helps de-risk the technology narrative. It is worth noting, however, that the product remains at the testing and proof-of-concept stage rather than a revenue stage, and no financial figures or contract values have been disclosed.
The Company’s recent nil-discount placement, which raised $15 million at $0.715 per share with enterprise design partner engagement flagged as a Q4 FY26 priority, provides the capital runway that makes the Version 1.0 testing phase commercially meaningful rather than a purely technical exercise.
By way of context, FortifAI is an ASX-listed technology company focused on artificial intelligence and advanced computing. It develops AI technologies through its subsidiary Nol8, alongside a broad portfolio of video games.
Alon Rashelbach, Founder and CTO, Nol8
“Agentic AI is creating a new infrastructure requirement: petabytes of data must flow into AI systems continuously, safely, and under control, with response times measured in milliseconds. The AI Data Plane is built for that requirement, delivering wire-speed governance for AI data with breakthrough algorithms accelerated by specialized cloud hardware. We are now testing it with our first design partners.”
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