Fobi AI Introduces FIXYR And Advances Its Transition Into A Lean, Enterprise-Focused Artificial Intelligence Platform AGORACOM Small Cap CEO Interviews podcast

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Fobi AI Introduces FIXYR and Advances Its Transition Into a Lean, Enterprise-Focused Artificial Intelligence Platform

14h ago 59:12

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Fobi AI CEO Rob Anson outlines how the company has progressed from internal restructuring to early commercial validation, marked by the live deployment of FIXYR, its first autonomous enterprise support platform. While operating under regulatory constraints, management continued executing on its strategy, preserving revenue, materially reducing costs through Artificial Intelligence automation, and moving from internal transformation to externally validated use cases.The interview presents a business that differs meaningfully from the one investors last evaluated. Rather than pausing during a period of restricted trading, the focus remained on strengthening the company’s financial profile, advancing its technology stack, and building deployable Artificial Intelligence systems designed to deliver clear, measurable value for enterprise customers.EXECUTION THROUGH CONSTRAINT, NOT PAUSEA central theme of the discussion is how Fobi maintained momentum during a period of limited market visibility. In 2024, the company generated nearly $3 million in revenue while management reports annual operating costs were reduced to approximately $1.1 million through deeper integration of Artificial Intelligence across internal operations. This leaner cost structure materially improves operating leverage and positions the business for scalable growth as activity normalizes.Fobi recently announced a $1.5 million non-brokered private placement to support audit completion and regulatory requirements. Management indicated that the audit process is nearing completion, positioning the company for a full revocation order, relisting, and a return to normal trading.Fobi AI 3.0: FROM ADVISORY TO DEPLOYED SYSTEMSThe interview marks the company’s transition to what management describes as Fobi AI 3.0. Rather than operating primarily as a consultant, Fobi now delivers both the strategic architecture and the deployed Artificial Intelligence systems themselves. This integrated model is designed to reduce implementation risk, shorten deployment timelines, and lower total cost of ownership for enterprise customers.A key differentiator highlighted is Fobi’s emphasis on building and training proprietary Artificial Intelligence models, rather than relying exclusively on third-party platforms. This focus on data control and sovereignty directly addresses a major adoption consideration for regulated, privacy-sensitive, and enterprise-scale organizations.FIXYR: EARLY COMMERCIAL VALIDATIONAt the center of the discussion is FIXYR, Fobi AI’s autonomous Artificial Intelligence customer service and technical support platform. FIXYR is designed to automate labor-intensive support workflows through real-time, self-resolving processes.In its initial large-scale live deployment, management reported that FIXYR processed more than 20,000 digital tickets, handled over 200 customer inquiries, maintained reported 100 percent system uptime, achieved reported 100 percent customer satisfaction, and operated with no frontline human intervention.Management noted that this deployment replaced the workload equivalent of a support operation of approximately 35 staff, translating into roughly 90 percent cost savings for the operator. For investors, FIXYR represents a meaningful step from concept to early, measurable return on investment.BUILT FOR RELIABILITY, CONTROL, AND REPEATABILITYBeyond FIXYR, Fobi emphasized its broader Artificial Intelligence infrastructure, designed for reliability and repeatability in enterprise environments. By training proprietary models in-house and using simulation-driven development to test outcomes prior to deployment, the company aims to reduce execution risk while improving consistency.This approach is particularly relevant for regulated industries where data governance, auditability, and operational certainty are critical to adoption.

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