ARway.ai The Spatial Computing Platform Signs New Deal with Saudi Arabian Agency for AR Navigation

New episode of CEO Experience Podcast Highlights Apple Vision Pro x ARway

CIO Review

New episode of CEO Experience Podcast Highlights Apple Vision Pro x ARway

TORONTO, ON, Canada – ARway.ai (“ARway” or the “Company”) (CSE: ARWY), (OTC: ARWYF) (FSE: E65) is an AI powered Augmented Reality Experience platform with a disruptive no-code, no beacon spatial computing solution enabled by visual marker tracking with centimeter precision is pleased to announce a new deal with AI Safer, the esteemed Agency of Record for The Royal Institute of Traditional Arts in Saudi Arabia. This collaboration marks a significant step in enhancing visitor experiences at museums and tourist attractions across Saudi Arabia through state-of-the-art AR navigation technology.

AI Safer, renowned for its commitment to innovative and safe technological solutions in the realm of arts and culture, has chosen ARway for its expertise in creating immersive and interactive AR environments. This contract will see the integration of ARway's cutting-edge navigation technology in key cultural sites, offering visitors a unique, engaging, and educational experience.

ARway CEO Evan Gappelberg commented, "ARway is excited to partner with AI Safer and The Royal Institute of Traditional Arts to bring our advanced AR navigation to the rich cultural landscape of Saudi Arabia. Our technology will enable visitors to explore museums and attractions in an entirely new way, making each visit more informative, interactive, and enjoyable. This deal truly showcases the global scale of our technology and the continued increase in demand we’ve been seeing throughout the world for various use cases and industries."

The implementation of ARway's navigation technology is set to begin in March 2024.

This initiative aligns with Saudi Arabia's Vision 2030, which emphasizes the development of the cultural sector and the enhancement of the tourism experience. The AR navigation system will guide visitors through various exhibits and points of interest, providing contextual information and interactive elements to deepen their understanding and appreciation of Saudi Arabia's rich cultural heritage.

Watch a video demo of an AR museum experience created by ARway - click here

Apple Vision Pro

In September 2023, ARway announced the Company was selected to participate at Apple’s Vision Pro Developer Labs in Cupertino, California. As a result, ARway completed a first build of the ARway Platform on Apple's Vision Pro hardware and realityOS operating system. ARway currently delivers optimal performance on iOS devices and will seamlessly integrate into Apple's ecosystem.

Apple announced Apple Vision Pro will be available beginning Friday, February 2nd, at all U.S. Apple Store locations and the U.S. Apple Store online. CEO Evan Gappelberg commented: "The long awaited Apple AR glasses are here! We have been waiting for this moment since 2019 and I’m extremely excited to announce that it has finally arrived. I see this as an enormous opportunity for early investors to participate in the next big thing… augmented reality and spatial computing technology. ARway is purpose built for the Vision Pro Launch. "The consumer adoption of “Apple Vision Pro“ will be a massive boost for the augmented reality industry, opening up a new market opportunity for ARway’s technology as the Company is a software solution provider for the Apple Vision Pro. ARway.ai’s use cases in indoor navigation and recent efforts have focused precisely on AR glasses integration, aligning the Company’s vision and execution with the industry shift to 3D/AR.

Public Company CEO Experience Podcast

A new episode of the Public Company CEO Experience podcast is now available!

Episode 6: ARway.ai Update on Apple Vision Pro Launch

Click here to listen

In this episode, CEO Evan Gappelberg provides a progress report on ARway.ai, as well as what the imminent launch of Apple Vision Pro will mean for the company going forward. As the Apple launch is only weeks away from the recording of this episode, Evan also provides additional detail around the ARway.ai patented augmented reality spatial computing platform, increased adoption rates across a growing customer portfolio, and how the company is well poised to be the leader in indoor wayfinding.

About the Public Company CEO Experience Podcast

“The Public Company CEO Experience Podcast” offers listeners an exclusive behind-the-scenes look into the dynamic life of a public company CEO with valuable insights, while also discussing trending topics and providing business updates on Nexech3D.ai, Toggle3D.ai, and ARway.ai.

From groundbreaking technological advancements to key industry updates, the podcast aims to foster a deeper understanding of the AR and AI technology landscape and its potential impact on various sectors.

Nextech3D.ai invites professionals, investors, and technology enthusiasts to tune in to "The Public Company CEO Experience Podcast" for an immersive journey into the world of public company leadership. With each episode, listeners will gain invaluable perspectives and knowledge, empowering them to make informed decisions and stay ahead of the curve. To learn more please visit https://www.nextechar.com/investors/the-ceo-experience

Subscribe to the Podcast

https://www.nextechar.com/the-ceo-experience/subscribe

The podcast is available on the following major podcast platforms:

Spotify - listen here

Amazon Music - listen here

Podcast Index - listen here

Podcast Addict - listen here

Podchaser - listen here

Pocket Casts - listen here

Deezer - listen here

Listen Notes - listen here

Player FM - listen here

Youtube - listen here

Sign up for Investor News - HERE

To learn more about ARway, please follow on Social Media: Twitter, YouTube, Instagram, LinkedIn, and Facebook, and visit our website: www.arway.ai

More in News

Making AI Agents Accountable to Workflows

AI agents are exposing a problem that conventional workflow software has rarely solved. Many enterprises run essential work across SaaS platforms, integration tools, local scripts and shared spreadsheets. Agents are then expected to work across all of them, gather enough context and make safe decisions. The difficulty lies in the gap between what an agent can infer and what the business can actually control. Point-to-point integrations move data but do not preserve the history of a process. iPaaS platforms connect systems, yet long-running work can still end up scattered across queues, callbacks, approvals and exceptions. For buyers, introducing agents is only part of the challenge. They also need a process that can show exactly what happened. Workflow orchestration can provide that structure when it carries context along with the work instead of simply routing it from one system to another. Agents still need room to exercise judgment, but that judgment needs boundaries. A model might classify an email, interpret intent, retrieve missing context and recommend what should happen next. It should not have to work out the refund procedure or customer verification process from scratch every time a request comes in. Repeatable steps are less expensive to execute through deterministic logic and easier to audit. The agent can then handle the parts that require interpretation while established actions remain within versioned process logic. “Agents can make decisions where judgment is required while the workflow handles repeatable actions.” That separation is useful only if the business can see what happened in each workflow. Executives need a way to inspect the process template, runtime history, agent decision and failure path in one place. Once APIs, agents, human reviewers and external events are involved, ordinary system logs do not provide the whole picture. Buyers need to know which action ran, what data moved, what decision was made and what happened when a step timed out or had to be retried. Keeping that information with the process also makes automation easier to improve because performance data remains connected to the work that produced it. The amount of engineering required to get there matters too. An orchestration platform has limited practical value if a company needs to build a large specialist team before it can put a useful process into production. Existing services and SaaS APIs should be composable into business logic that people can understand and change without rebuilding the entire integration map. A code-first approach is useful when software teams get version control, business reviewers can see the workflow as a visual graph, auditors can trace what happened and agents have a stable process map to work within. The larger issue is ownership of the process, not simply how many tasks can be automated. Long-running workflows need to retain state, and agent decisions need to remain visible without requiring a model call at every step. Once the process is running, event-driven feedback can show where it needs improvement. The platform also has to work for organizations with different levels of software maturity. One team may be coordinating a large collection of microservices, while another needs custom workflow logic around ERP, CRM, field-service and workforce systems without having to wait for a vendor to add the functionality to its roadmap. LittleHorse takes this approach with Saddle Command Center and its Business-as-Code model for building workflows across microservices, SaaS platforms, agents and human-in-the-loop steps. Agents can make decisions where judgment is required while the workflow handles repeatable actions. Individual instances remain traceable, and workflow event data can be published to Apache Kafka for analysis. Support for Java, Python, Go and C# also allows engineering teams to maintain the business logic without having to adopt a specialist workflow language. For enterprises working across disconnected SaaS environments or complex microservice estates, LittleHorse provides a practical way to give AI agents room to make decisions while keeping the surrounding process visible and controlled. ...Read more

Cloud Control for Sage Environments without Vendor Sprawl

Sage migration decisions often begin with a contradiction. Finance and IT teams want the subscription feel of SaaS, yet the applications they rely on still carry custom workflows, connected databases, reporting routines and partner-managed changes. A generic cloud host can move the server, but it may leave the business managing every handoff when access breaks or latency appears during a critical task. Month-end close, warehouse workflows, payroll access and reporting cycles leave little room for cloud experiments that behave well only under ideal conditions. The weak point is usually not migration itself. It is the support chain that follows. Servers sit somewhere, a hosting provider manages the platform, the software publisher owns the application, a Sage consultant handles business logic and the internal team is left to coordinate the room. A single interruption then becomes a routing problem. Executives should favor a hosting model that reduces escalation layers without stripping away control over the ERP. Control matters because Sage environments rarely behave like standard SaaS tenants. Updates, integrations, VPN links, reporting tools and adjacent applications may need business-specific treatment. Shared resources can look efficient until they limit troubleshooting or change windows. Dedicated virtual environments, network isolation, clear backup design and documented availability standards give leadership a firmer basis for risk decisions. The point is not more infrastructure for its own sake. It is a service model that keeps customization possible while making ownership clearer. Ransomware risk and phishing exposure have changed the due diligence standard for hosted ERP. Sage access cannot be separated from identity controls, recovery routines, monitoring practices and response authority. A provider that only hosts the application may still leave security teams stitching together evidence after an incident. Before renewal terms are signed, buyers should test how backup frequency, network segmentation, disaster recovery design and incident escalation work in practice. Cloud economics create a second trap. Public cloud flexibility can turn into variable outlay when workloads are poorly matched to the platform. Licensing shifts and Microsoft choices make architecture a finance issue as much as an IT issue. Lowest monthly price can be misleading when internal staff must manage exceptions or pull multiple suppliers into every problem. A stronger decision weighs contract predictability, application performance, recovery posture and the cost of internal coordination. Sage projects also require a provider that can work alongside ERP partners rather than displace them. Against that buying logic, Cloud at Work is a premier choice for Sage cloud hosting. It model is built around Sage end users and fewer support handoffs, then extended that base into Azure and managed technology services where the customer environment demands it. Its portfolio spans Virtual Private Cloud, Infrastructure as a Service, Desktop as a Service, Managed Services and Managed Cybersecurity, giving buyers a path from hosted Sage to broader cloud management without changing accountability every time the environment expands. Dedicated resources, virtual firewalls, backup design and Sage-aware support match the pressures that matter most. For leaders who want Sage to feel closer to a managed service while preserving customization, Cloud at Work warrants serious consideration. ...Read more

Digital Transformation That Canada’s Enterprises Can Govern

Digital transformation remains a priority for organizations across Canada, but for many leaders, the challenge is no longer deciding whether to modernize. It is figuring out how to do it without disrupting the systems the business relies on every day. Many organizations are operating in a mixed environment where old and new technologies must work side by side. Core applications that were implemented years ago still support critical operations. ERP and commercial off-the-shelf platforms have been customized over time to fit unique business processes. Data often lives in multiple systems and cybersecurity concerns continue to grow as organizations expand their use of cloud services, mobile applications and external partners. The result is a level of complexity that can make modernization feel risky, even when change is clearly needed. This is why successful digital transformation rarely starts with technology. It starts with understanding the business. Leaders need a clear picture of which systems continue to deliver value, where inefficiencies exist and which investments will have the greatest impact. Organizations often spend too much money replacing systems that still serve an important purpose or implementing new solutions before fully understanding the long-term costs. The most effective transformation partners help organizations make informed decisions rather than pushing change for its own sake. The same practical approach applies to emerging technologies such as artificial intelligence. While AI continues to attract attention, its success depends heavily on the quality of the data behind it. Organizations that struggle with fragmented information, inconsistent processes or weak governance often find it difficult to unlock meaningful value from AI investments. Data modernization, cybersecurity and system modernization are closely connected. Progress in one area often depends on getting the others right. Security has become another defining factor in successful transformation initiatives. Whether operating in healthcare, education, municipal government or the private sector, Canadian organizations face increasing expectations around privacy, access management and accountability. Security cannot be treated as a separate project that follows modernization efforts. It needs to be built into planning and decision-making from the beginning. Strong governance, clear documentation and defined responsibilities help organizations reduce risk while giving leadership teams confidence that projects remain on track. Execution is equally important. Many transformation initiatives struggle not because the strategy is wrong but because employees are left behind during the process. New systems, workflows and technologies only create value when people understand how to use them and why the changes matter. Clear communication, realistic timelines and strong change management are often the difference between a successful implementation and an expensive disappointment. For organizations operating across different regions of Canada, bilingual communication and local stakeholder engagement can further influence outcomes. For organizations looking to modernize in a practical and manageable way, IPSG Technology offers an approach grounded in business realities rather than technology trends. The company combines custom application development, website modernization, cloud services, cybersecurity, data optimization and change enablement to help organizations navigate complex transformation initiatives with confidence. Its strength lies in helping clients modernize ERP and COTS environments without unnecessary replacement, align AI initiatives with data readiness and incorporate security from the outset. By focusing on clarity, governance and measurable outcomes, IPSG Technology helps organizations move forward without losing sight of operational continuity, budget control and long-term business value. ...Read more

From Fragmented Data to Timely Decisions

Mid-sized companies often reach a point where data volume has outgrown the reporting habits built around it. Sales systems, finance platforms, customer records and workforce tools accumulate information, yet decision-makers still wait for manually assembled reports or rely on partial views. The buying problem is rarely a shortage of software. It is the cost and coordination burden of connecting systems, preparing reliable data and turning it into useful action without building a large specialist team. Platform selection should begin with the data foundation. Dashboards and AI models cannot compensate for inconsistent definitions, missing records or poorly governed pipelines. Executives need to know how a platform profiles and cleans data while preserving traceability from source to output. Integration also matters beyond the initial connection. A workable platform must support existing databases and business applications while reducing the amount of custom code required to keep those links current. Migration demands, refresh frequency and access controls deserve scrutiny before implementation begins. The next pressure is time to proof. Many firms cannot justify a large upfront investment in engineers and data scientists before a use case has shown credible returns. A platform should let a business test a narrow problem and measure model accuracy before committing to broader deployment. Low-code workflow design can shorten that cycle, but ease of configuration must not remove oversight. Buyers should examine how knowledge bases and semantic layers are managed when model outputs affect staff decisions or customer-facing processes. Access to insight presents a separate test. Static reports remain useful for recurring review, yet business leaders increasingly need answers that were not anticipated when a dashboard was built. Natural-language querying can reduce dependence on report backlogs, provided the platform grounds responses in governed company data and shows enough context for users to judge the result. Predictive functions should be assessed in the same manner. Forecasts are valuable only when teams can understand the inputs and monitor performance before connecting a prediction to a defined next step. The final buying concern is service depth. Mid-sized firms may adopt a capable platform and still lack the people to design data models or maintain AI workflows. A provider should be able to supply targeted support without turning every change into a consulting project. Subscription or usage-based pricing can lower the entry barrier, though buyers should compare consumption controls and support terms carefully. The strongest fit will combine self-service tools with practical help around implementation and model tuning, backed by ongoing maintenance when internal capacity is limited. Aidas Technologies is a premier choice for firms that need this combination without assembling separate platforms and specialist teams. Its AI-powered data and analytics platform brings data preparation, reporting, predictive modeling and workflow automation into one environment through low-code tools. The company also offers professional services for setup and custom development, plus model support and continued maintenance, allowing buyers to test focused use cases before scaling. A usage-based subscription model further suits mid-sized organizations that need tighter control over upfront cost. For executives prioritizing faster proof and guided adoption, Aidas Technologies merits serious consideration. ...Read more