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Hype is loud, but outcomes win. We sit down with Smartling CEO Bryan Murphy to explore why the center of gravity in AI is shifting from raw models to the application layer where workflows, data, and governance translate into real business value. If you’ve been stuck in pilot purgatory, you’ll hear how to move from experiments to production with clear ROI.

Bryan draws sharp parallels to earlier waves—the internet and cloud—and explains how today’s “chips and data centers” moment mirrors the 90s buildout, with a familiar follow-up: purpose-built apps that make the infrastructure usable. We dig into translation as a top-tier AI use case and unpack Smartling’s results: translating 3x more content at about 60 percent less cost and six times faster than traditional methods. The secret isn’t a flashy bolt-on; it’s re-architecting around an AI hub and agentic workflows that integrate directly with enterprise stacks.

We also challenge the “AI will kill SaaS” headline. Foundational models like GPT and Claude are treated as infrastructure, while the real differentiation comes from orchestration—selecting the best model for the job, routing data safely, learning from feedback, and guaranteeing quality. Bryan shares how governance protects brand voice at scale, from hallucination detection to automated language QA and custom-trained models honoring glossaries and style guides. With 7 billion words translated a year, reliability isn’t a feature—it’s the product.

Looking ahead, we explore multimodal translation across text, audio, and video, and a future where translation functions as a service embedded in everyday tools. For founders, Bryan offers practical advice: target a 10x problem, verify there’s real TAM, and build applications that customers will happily pay for. For enterprise leaders, the message is simple: stop chasing models, invest in orchestration, and pick solutions that measure and deliver outcomes.

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