Verses Ai Inc · NEO:VERS

Verses Ai — Corporate Update (February 2026)

20 slides from Verses Ai's corporate update, Feb 18, 2026

  1. Slide 1: Q1 2026 Webinar

    Q1 2026 Webinar 18-February-2026 OTCQB:VRSSF CBOE:VERS ©2026 VERSES AI, INC Confidential and Proprietary.

  2. Slide 2: Forward looking information disclaimer

    Forward looking information disclaimer This presentation contains "forward-looking information" and "forward-looking statements" within the meaning of applicable securities legislation (collectively, “forward-looking statements”). Forward-looking statements can be identified by the use of words such

  3. Slide 3: Agenda

    Agenda 1. Changes to VERSES leadership 2. Fundamental science 3. Go to market strategy 4. Questions and answers

  4. Slide 4: Change of leadership

    Change of leadership ● Change of leadership. ● Search for permanent CEO underway. ● David T. Scott Interim CEO.

  5. Slide 5: Introducing David T. Scott

    Introducing David T. Scott ● Interim CEO. ● Board member since October 2025. ● 30-year career spanning Amazon Web Services, Twitter, AT&T, and multiple public and private technology companies. ● Creating value by turning complex technology into scalable, repeatable revenue.

  6. Slide 6: Overview

    Overview ● More direct communication. ● Earnings call next Tuesday February 24, 2026. ● Progress on R&D. ● Focus on financial services. ● Our go to market strategy and business model.

  7. Slide 7: Our fundamental science

    Our fundamental science

  8. Slide 8: Our progress

    Our progress ● Results: ○ AXIOM digital brain - beat Google AXIOM vs Deepmind DeepMind. ● 60% better ● 39 times faster in GPU runtime ○ Habitat - underlying technology ● 39 times Cheaper to run applied to robotics. ● R&D team focused on applied product development. ● Capabilities with broad applicab

  9. Slide 9: ARC-AGI-3

    ARC-AGI-3 ARC-AGI-S5 Interactive Reasoning Benchmark Measuring interactive human-like intelligence in Al Coming March 25, 2026

  10. Slide 10: Moving from science to code

    Moving from science to code ● Professor Friston’s work shows how the natural systems learn, and make decisions in the world. ● AXIOM is like the early development of electrical infrastructure. ● Product is an engineering challenge to make the code effective and useful.

  11. Slide 11: Genius: Applied

    Genius: Applied ● We applied Genius across many industries, verticals, and markets as part of our commercial beta program in 2025. ● Areas like the Spatial Web, Robotics, Supply Chain and others take a back seat. ● Focus on the financial services space. ○ Financial services has interest in using AI

  12. Slide 12: Go to market

    Go to market

  13. Slide 13: The portfolio management market

    The portfolio management market ● A modest improvement in the return of even a $100m portfolio can justify significant investment in better decision-support systems ● Financial services represent a large addressable opportunity in the multi trillion dollar global asset management market.

  14. Slide 14: Genius for financial services

    Genius for financial services ● Target customers see our approach Genius helps portfolio managers to as highly differentiated. make more confident decisions ● Current AI systems used in finance often operate as black boxes. ● Our active inference–based technology explicitly quantifies uncertainty an

  15. Slide 15: Financial services progress

    Financial services progress ● We have worked closely with a global Explicit modelling of risk and portfolio manager overseeing more uncertainty builds customer trust in models than $100 billion in assets under management. ● Revenue from August 2025. ● We believe this shows: ○ Positive indicators of

  16. Slide 16: Commercialization of Genius for financial services

    Commercialization of Genius for financial services ● Expand with our current financial services customer. ● Target comparable institutions — particularly portfolio managers with more than $100m in assets. ● Explore further channel partnerships.

  17. Slide 17: Business model

    Business model ● Hybrid approach: ○ Services and implementation component ○ Recurring software licenses. ● Computational efficiency: operating costs are relatively low and stable compared to alternative AI approaches. ● Technology validated in real enterprise environments.

  18. Slide 18: Wrap up

    Wrap up

  19. Slide 19: Questions

    Questions

  20. Slide 20: Earnings Call - Tuesday Feb 24, 2026

    Earnings Call - Tuesday Feb 24, 2026

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