Fortifai Limited · ASX:FTI
Fortifai — Noosa Investor Conference 2026
17 slides from Fortifai's conference presentation, Oct 14, 2026
Slide 1: The AI Data Plane: The Control Point for AI
The AI Data Plane: The Control Point for AI Investor Presentation – Noosa Investor Conference October 2026 | FortifAI Limited (ASX: FTI) www.nol8.io
Slide 2: Behind every AI task is a world of enterprise data
Behind every AI task is a world of enterprise data. Train Data that trains it Infer Information it draws on Act Content it creates FortifAI Limited (ASX: FTI) www.nol8.io 2
Slide 3: Market Opportunity
Market Opportunity Agentic AI is a US$4 trillion market. Our TAM, the data layer, is US$120bn. Artificial Intelligence Market Size, US$ billion US$4T 3,680 US$4.4T Value of Agentic AI by 2030 (McKinsey) 3,077 2,156 2,575 96% CAGR Agentic Token Growth, 2026 to 2030 (Goldman Sachs) 1,807 1,516 1,273 7
Slide 4: The Market has Named the Bottleneck to Enterprise AI Adoption: DATA
The Market View The Market has Named the Bottleneck to Enterprise AI Adoption: DATA “Surround non-deterministic models with deterministic controls, “ observability, privilege limits, logging, and the ability to always contain or shut them down.” The data layer represents both the David Sacks Investo
Slide 5: The data requiring processing is compounding. 90% of it is unstructured.
Data Layer Growth The data requiring processing is compounding. 90% of it is unstructured. Global Datasphere (Zeta bytes per year) 19,267 ZB Processing unstructured data is the most compute intensive. 58x in Ten Years 90% 90% Unstructured 10% Structured 2,537 ZB 334 ZB "About 90% of what's generated
Slide 6: What is Unstructured Data?
What is Unstructured Data? What is Unstructured Data? Structured Unstructured Customer ID Name Account Balance Status C-10421 J. Smith •••• 4417 $12,400 Active C-10422 A. Nguyen •••• 9021 $3,150 Active C-10423 R. Patel •••• 2276 $48,900 Review C-10424 L. Chen •••• 6610 $7,035 Active C-10425 M. Rossi
Slide 7: Enterprise AI currently only uses the tip of the iceberg
The Enterprise Data Iceberg Enterprise AI currently only uses the tip of the iceberg. ≈10% Utilised NOL8 makes the other 90% usable. Data use minimised due to regulatory concerns. Unstructured data must remain submerged because enterprises can’t control what agents do with it. NOL8 checks every byte
Slide 8: Enterprise AI Adoption Won't Exist Without True Governance of Data
The Bottleneck Enterprise AI Adoption Won’t Exist Without True Governance of Data. September 2026 Enterprises need agents but they won’t let agents near sensitive data until they can demonstrate complete control and an ability An AI agent gets into a Medicare portal to audit it afterwards. An OpenAI
Slide 9: Data must be controlled before AI can use it
How We Solve It Data must be controlled before AI can use it. The customer defines what may pass via policy (rule) enforcement. Inspect · Enforce · Log AI Applications and Agents One giant enterprise data corpus AI Data Control Plane Illustrative workflow. Rule coverage and supported actions depend
Slide 10: Why We Win: 100% accuracy, every byte, at any scale
The Enterprise Requirement - Why We Win Why We Win: 100% accuracy, every byte, at any scale. Data The Check AI What’s Returned Accuracy As Rules Grow Today A classifier scores it, for A guardrail scores the rules → Probabilistic, on CPUs and example "0.74 confidence". answer: probabilistic, GPUs Lim
Slide 11: Independent Verification - Economics
Independent Verification - Economics NOL8 Independently verified: up to 118x more data processed per dollar. Infrastructure cost, US$ per GB/s of throughput per hour (log scale) US$1000 118x RE2 US$240 More data per infrastructure dollar than Google RE2 at 5,000 rules; 4.1x at 128, widening at every
Slide 12: Superior Features and Total Cost Ownership for the customer
How the Market Prices Governance · Why We Win Superior Features and Total Cost Ownership for the customer. US$ per GB: What Enterprises Pay For Current Solutions - against NOL8s indicative price (pricing is yet undetermined). Superior Features and Cost for the Customer Amazon Macie US$1.00 • Every b
Slide 13: Megaport and Equinix: Our Introduction to Thousands of Customers
Channel to Market Megaport and Equinix: Our Introduction to Thousands of Customers Full Availability on Equinix Megaport and Equinix networks on Version 2.0 Release. Megaport ASX: MP1 Equinix Nasdaq: EQIX Joined June 2026 Joined September 2026 ~A$4.5bn 3,200+ 1,100+ ~US$101bn 10,500+ 282 Market Cap
Slide 14: Delivering Ahead of our Roadmap to Revenue
Roadmap Delivering Ahead of our Roadmap to Revenue. Delivered Delivered October release Target Target Feb Mid October End Mar Q 2026 2026 2026 CY2026 2027 $ Demonstration engine Version 1.0 Version 2.0 First customer contracts First revenue Benchmarking engine ready for Targeted Targeted Targeted cu
Slide 15: A team that has built and scaled before
Team A team that has built and scaled before. Leadership Advisory board Kelly Herrell Alon Rashelbach Jamie Pope Jason Brushe David Walker Former CTO, Westpac Chief Executive Officer Co-founder and CTO Chief Solutions Officer Technical Advisor Former executive director, DBS Bank. Chairs the UNSW AI
Slide 16: Corporate Snapshot
Corporate Snapshot FortifAI Limited (ASX: FTI) A$0.58 ~398m 12-month share price, A$ $1.40 Share Price Shares on issue ~A$231m ~615m $1.05 Market capitalisation Fully diluted shares $0.70 ~A$357m A$20.4m Fully diluted market cap Cash, 30 Jun 2026 $0.35 Nil ~A$211m Nov 25 Dec 25 Jan 26 Feb 26 Mar 26
Slide 17: Disclaimer
Disclaimer Authorised for release by the Board of Directors of FortifAI Limited. Statements contained in this document, including but not limited to those regarding the possible or assumed future costs, performance, dividends, returns, revenue, exchange rates, potential growth of the Company , indus