Why ‘We’re Not Ready Yet’ No Longer Cuts it in 2026’s AI Landscape
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In 2026, saying “We’re not ready for AI” is like saying “We don’t need the internet” in 2000. It’s not a strategic stance – it’s a signal that the world is moving faster…
The Trust Gap and the Compliance Firewall: Why interface.ai is THE Safe Choice for Financial AI
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In the rush to adopt generative AI, financial institutions have discovered a sobering reality: General-purpose AI is a liability in a regulated environment. While a standard Large Language Model (LLM) might confidently offer…
Agentic AI: The Banking Innovation Everyone Is Talking About
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For years, financial institutions have heard big promises about AI – smarter service, lower costs, faster resolution. But the tools never fully delivered. Early “AI” was really just chatbot logic wrapped in marketing…
Beyond the Link: Why Multi-Granular Retrieval is the Future of Member Service
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In today’s market, your Voice AI and chatbot systems are the frontline of your member experience. A modern member expects a precise, contextual answer in seconds, not a link to a generic webpage….
The Trust Paradox: How Agentic AI is Making Banking More Human
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For years, people were right to be skeptical about AI in banking. Early automation was rigid, scripted, and anything but personal. It did make service feel less human. But 2026 is a different…
interface.ai Named in 2025 CB Insights’ List of the 100 Most Promising Fintech Startups
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About interface.ai Founded in 2015 in California by Srinivas Njay (a former banker and ex-Microsoft) and Bruce Kim (AI veteran with 25+ years in enterprise systems), interface.ai was built with a singular focus:…
The Agentic AI Shift: Out With Self-Service, in With Self-Resolution
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For years, “self-service” has been the north star for digital banking. IVR menus. Mobile apps. FAQ pages. Basic chatbots. These tools were meant to give members and customers independence – a way to…
Call Center AI in Banking: From Cost Center to Growth Engine
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For years, call centers in banking have been viewed as essential but expensive – a necessary function that supports customers but is difficult to scale without adding more people, training, and cost. As…
