The OLB Group Reports Second Quarter 2026 Results and Completes Company-Wide Transition to AI-Assisted Software Development

About this update from The Olb Group, Inc.

Net Loss Narrows 50.3% and Operating Expenses Decline 23.4% Year Over Year NEW YORK CITY, NY / ACCESS Newswire / August 17, 2026 / The OLB Group, Inc. (Nasdaq:OLB) ("OLB" or the "Company"), a financial technology company providing integrated payment processing and merchant services solutions throughout the United States, today announced financial results for the second quarter and six months ended June 30, 2026, and provided an update on the Company's transition to an artificial intelligence-native operating model. For the second quarter of 2026, the Company reported total revenue of $1,279,251 and a net loss of $1,054,806, compared to total revenue of $2,267,191 and a net loss of $2,124,314 for the second quarter of 2025. Net loss per share improved to $(0.08) from $(0.66). For the six months ended June 30, 2026, net loss narrowed to $2,132,388 from $3,213,312 in the prior-year period. Total operating expenses for the six months ended June 30, 2026 were $5,465,351, a decrease of $1,668,801, or 23.4%, from $7,134,152 in the prior-year period. Cash increased to $1,280,226 at June 30, 2026 from $15,777 at December 31, 2025, and total stockholders' equity increased 55.1% to $7,142,171. Based on the Company's liquidity position and recent capital-raising activities, management concluded that substantial doubt about the Company's ability to continue as a going concern does not exist. Second Quarter and Recent Highlights Transition to AI-Assisted Software Development Beginning in 2026, the Company transitioned its entire software development team, across both business segments, to an artificial intelligence-assisted model for developing and maintaining its applications, a methodology commonly referred to as "Agentic Coding": engineers direct and review code generated by large language model tools rather than authoring it, with AI agents supporting scaffolding, refactoring, testing and documentation. The Company is hiring and training engineers to build and orchestrate agentic systems, and believes these methods may compress development cycles, reduce engineering cost per feature delivered and accelerate delivery of merchant-specific solutions, though it has limited operating history with them and can provide no assurance those benefits will be realized. Agentic artificial intelligence is also being deployed across customer support (onboarding inquiries, ticket ...

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