VANCOUVER, British Columbia, July 29, 2025 (GLOBE NEWSWIRE) — VERSES AI Inc. (CBOE: VERS) (OTCQB: VRSSF) (“VERSES” or the “Company”), a cognitive computing company specializing in next-generation agentic software systems releases a shareholder letter ahead of the corporate webinar today, Tuesday June 29th at 9:30am PT/12:30pm ET.
Shareholder Update Summer 2025
Thank you to all of our investors and stakeholders who have supported us during the last few years, and especially during the most recent challenging times. We are hosting a webinar today and look forward to discussing these points in more detail and we encourage you to join us using this link: Here
We are at day 1 of AI
When we founded VERSES we were excited by the possibilities that AI and Spatial Computing offered to make the world smarter and better and we have been working hard to try to make that vision a reality.
While some types of AI have become mainstream seemingly overnight, in our view, Enterprise AI adoption has, so far, been slow, especially for important tasks such as running a business, driving a car or logistics.
In our view, slower than expected adoption isn’t because of a lack of interest from large companies, but rather it is because Large Language Models (LLMs), while an incredible achievement, do not really perform tasks and are not reliable for many purposes.
VERSES approach is based in science
We believe our strategy is different and unique from other AI companies, so it’s natural that many people still need to understand the full scope and application of what we are developing here at VERSES.
We drew inspiration from human intelligence for a simple reason. Evolution has invested millions of years into brains and bodies that are efficient at thriving in our world. That’s why, for example, a human brain operates on only 20 Watts. And it is why we can quickly adapt to a changing environment.
Karl Friston, often listed as one of the world’s most cited neuroscientist, is our Chief Scientist. He and others have, over the last few decades, described this process as ‘active inference’.
The brain models the world and checks it against what it senses. To do this, the brain runs experiments. It assesses how well its model works. Then, it tests this model in the real world. Based on the results, it decides whether to keep the current model or update it to better match reality.
This process has been validated in multiple examples in numerous peer-reviewed journals demonstrating how actual neurons perform this process1, but people have generally believed these approaches are impossible to translate to computer science at a scalable level.
Proof that it’s working:
Proof #1: AXIOM
We recently unveiled what we believe is the world’s first digital brain, AXIOM. AXIOM has different modules for vision, memory, prediction and reasoning. These then recombine to work together to sense, reason, plan, act and learn.
In benchmarking, we have determined that AXIOM is more reliable and dramatically more efficient than other top models.
Proof #2: Spatial Web
Brains don’t just make models – they test them in the physical world.
That’s why we led the process to establish the new Spatial Web standards. which we believe will allow AI agents to work together to solve problems, safely and securely.
Proof #3: Customers
This approach isn’t theoretical – since the end of April we have started to sell it to enterprise customers through our product Genius™.
On use cases, we believe that our customers find Genius particularly useful where the data is uncertain, missing or volatile, and where they need a reliable and efficient solution.
We recently announced that a large global financial institution signed an enterprise agreement to model financial markets.
And we announced results of our pilot with Analog to optimize fleet management, which was estimated to create up to 32% better performance We believe smart cities can benefit from Genius, whether it’s optimally managing autonomous cars, sensors, drones and robotics, or energy in the smart grid.
Proof #4: Recognition
We are increasingly recognized by journalists and mainstream media.
WIRED called VERSES “A Deep Learning Alternative Can Help AI Agents Gameplay the Real World”. In that feature, François Chollet, creator of the ARC-AGI benchmark, told WIRED that
“The general goals of the [VERSES] approach and some of its key features track with what I see as the most important problems to focus on to get to AGI… The work strikes me as very original.”
What’s the next big thing?
We’ve shared with you how our technology can be applied to data problems, but one of the emerging frontiers, is robotics.
We encourage you to view an important video from our robotics team showing some early progress powering robots that can perform challenging tasks in real world scenarios, without training. You can view the video here: https://www.verses.ai/news/verses-announces-digital-brain-for-robotics.
Robots typically struggle to tackle challenges such as unanticipated objects in their way or a challenge not in their training data. Our approach promises to tackle this – and we expect to publish more information soon.
Thank you,
VERSES Team
About VERSES
VERSES® is a cognitive computing company building next-generation intelligent software systems modeled after the wisdom and genius of Nature. Designed around first principles found in science, physics and biology, our flagship product, Genius™, is an agentic enterprise intelligence platform designed to generate reliable domain-specific predictions and decisions under uncertainty. Imagine a Smarter World that elevates human potential through technology inspired by Nature. Learn more at verses.ai, LinkedIn and X.
On behalf of the Company
Gabriel René, Founder & CEO, VERSES AI Inc.
Press Inquiries: press@verses.ai
Investor Relations Inquiries
James Christodoulou, Chief Financial Officer
IR@verses.ai, +1(212)970-8889
Cautionary Note Regarding Forward-Looking Statements
This news release contains statements which constitute “forward-looking information” or “forward-looking statements” within the meaning of applicable securities laws, including statements regarding the plans, intentions, beliefs and current expectations of the Company with respect to future business activities and plans of the Company. Forward-looking information and forward-looking statements are often identified by the words “may”, “would”, “could”, “should”, “will”, “intend”, “plan”, “anticipate”, “believe”, “estimate”, “expect” or similar expressions.
The forward–looking statements and information are based on certain key expectations and assumptions made by the management of the Company. As a result, there can be no assurance that such plans will be completed as proposed or at all. Such forward-looking statements are based on a number of assumptions of management. Although management of the Company believes that the expectations and assumptions on which such forward-looking statements and information are based are reasonable, undue reliance should not be placed on the forward–looking statements and information since no assurance can be given that they will prove to be correct.
Forward-looking statements and information are provided for the purpose of providing information about the current expectations and plans of management of the Company relating to the future. Readers are cautioned that reliance on such statements and information may not be appropriate for other purposes, such as making investment decisions. Since forward–looking statements and information address future events and conditions, by their very nature they involve inherent risks and uncertainties. Actual results could differ materially from those currently anticipated due to a number of factors and risks. Accordingly, readers should not place undue reliance on the forward–looking statements and information contained in this news release. Readers are cautioned that the foregoing list of factors is not exhaustive.
The forward–looking statements and information contained in this news release are made as of the date hereof and no undertaking is given to update publicly or revise any forward–looking statements or information, whether as a result of new information, future events or otherwise, unless so required by applicable securities laws. The forward-looking statements or information contained in this news release are expressly qualified by this cautionary statement.
1 For instance Canonical neural networks perform active inference https://www.nature.com/articles/s42003-021-02994-2
