Most public companies slow down when a trading halt disrupts routine operations. Fobi AI did not. Even while operating under a cease-trade order that began November 1, 2024, the company continued to run the business, report revenue, and reshape how it intends to serve enterprise clients—an unusual combination of constraint and execution that has become central to its current story.
In an AGORACOM interview, Fobi President and CEO Rob Anson and Chief Technology Officer Uddeshya Agrawal described a year defined by cost discipline, operational restructuring, and the launch of a new customer-service automation platform. The conversation also outlined a broader positioning shift the company refers to as “Fobi 3.0”—a model that aims to combine enterprise advisory work with implementation under one roof.
A Company Built Around Real-Time Data and Digital Transformation
Fobi AI describes itself as an AI and data-intelligence company focused on helping organizations digitally transform using real-time applications, automation, and mobile-wallet capabilities. The company’s leadership framed this focus as increasingly relevant as more organizations attempt to modernize customer engagement, identity, and operational workflows—often across fragmented systems.
A key theme from the interview was that many organizations still lack a cohesive mobile-wallet strategy, which the company views as a practical gap in the market. That gap, the CEO suggested, is part of why the company believes its technology stack and services approach are timely.
Milestones Under Constraint: Revenue, Restructuring, and Lower Operating Costs
During the interview, Fobi’s leadership pointed to several concrete outcomes from the period:
- The company reported just under $3 million in revenue for 2024.
- It reduced its annual operating cost base to about $1.1 million, describing this as enabled by AI-driven automation and internal process changes.
- It continued building its next operating model while navigating the regulatory and audit work associated with the cease-trade order.
Anson described the last year as being consumed by legal, audit, and regulatory requirements, while the company simultaneously continued product and business development. He emphasized that management’s near-term focus was to complete the 2025 audit and proceed through the approvals required for a full revocation order and a relisting application process.
Moving Toward Trade Resumption: Audit Completion and Regulatory Steps
The interview discussed a recent announcement tied to a partial revocation order and a non-brokered private placement. Anson framed the timing as a practical step to help the company meet working-capital and process requirements connected to regulatory approvals.
He laid out a sequence of near-term milestones: completion of the audit, progression to a full revocation order, and the approvals required from the BCSC and the TSX Venture Exchange as part of the path back to trade resumption. While no fixed date was provided, he described the company as being near the end of the process, with legal and audit work in advanced stages.
“Fobi 3.0”: Combining Advisory and Implementation
A defining portion of the interview focused on what the company calls “Fobi 3.0,” which was described as a shift toward operating like an enterprise advisory partner that can also execute the solution—an approach Anson contrasted with large consulting models that often rely on third parties for implementation.
The positioning was summarized in plain terms: the company wants to advise on strategy, design the architecture, and implement programs—then measure outcomes. In the interview, this approach was compared to the enterprise footprint associated with large consulting firms, with the stated distinction that Fobi intends to be more integrated in execution rather than purely advisory.
Fixyr: A Launch Framed Around Automation and Service Continuity
The interview also highlighted the launch of Fixyr, which Fobi described as an AI-based customer service and technical support platform. The discussion avoided technical detail and instead focused on what the rollout looked like in practice and why the company built it.
The company cited performance metrics from an initial activation:
- Over 20,000 digital tickets processed
- Over 200 customer inquiries handled
- 100% uptime
- 100% satisfaction
- Zero human intervention
The use case described was tied to a large event environment where customer service volumes and staffing requirements can be difficult and expensive to manage. Anson stated that the platform enabled a shift away from a 35-person staffing requirement for that operational function, and he characterized the cost impact as roughly a 90% savings for the organizer, based on the company’s measurement and attribution.
Data Control, Privacy, and the Case for Internal Models
Another thread running through the interview was data sovereignty—control over how enterprise data is handled, where it flows, and who can train on it. Anson described privacy and confidentiality concerns as a major driver of demand among large organizations and presented this as one reason the company emphasized training its own model and building internal systems rather than relying only on general-purpose external tools.
Agrawal echoed the same philosophy in simpler language: many AI providers wrap a general model, while Fobi’s approach is to build and train its own systems for specific uses, including customer support—aiming to deliver responses based on context and history rather than generic scripts.
What Comes Next: Execution, Visibility, and Enterprise Pipeline
Looking forward, management emphasized continued disclosure of use cases and the operational benefits of what it has built, while also pointing to enterprise areas where the company is seeing interest—digital identity, finance and compliance-oriented workflows, aviation and transportation, sports and entertainment, and healthcare.
The company’s leadership also described a long-term operational goal of remaining lean—suggesting the business model is designed to scale without building a large headcount, supported by automation.
A Leaner Company Focused on Measurable Outcomes
Fobi AI’s recent narrative is unusually execution-heavy for a period dominated by regulatory, audit, and trading-halt constraints. The company’s leadership used the interview to frame a clearer operating model—one built around real-time systems, lower overhead, and a service approach that aims to connect strategy to implementation, then measure the impact.
Whether the next phase is defined by broader enterprise adoption or deeper proof through disclosed use cases, the company’s stated direction is consistent: build systems that keep operating when pressure is highest—and make the results visible, measurable, and repeatable.
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