SlatorPod

#283 Launching Welo Global with CEO Paul Carr

Paul Carr, CEO of Welo Global, joins SlatorPod to talk about the company’s strategic repositioning, continued AI investment, and evolving demand in the language solutions industry.Paul notes that the company has narrowed its focus to a few core areas and reorganized around client segments. He adds that client centricity and specialization have been central themes, alongside increased investment in AI and data engineering.The CEO highlights that two-thirds of Welo Global’s revenue now comes from outside of traditional localization departments. He says the business increasingly serves content owners such as legal teams, clinical managers, and AI labs.Paul describes the launch of Welo Global as a branding shift to reflect this broader scope. He explains that the new structure includes five client-facing brands tailored to specific industries and use cases, including Welocalize, Welo Data, Welo Life Sciences, Park IP, and Adapt.The CEO emphasizes that AI has driven major change, particularly through the development of the company’s Opal platform. He says the system delivers significantly higher-quality output than traditional machine translation by using agentic workflows and enterprise-specific data.Paul argues that localization ROI is difficult to isolate because it is usually part of broader investments like sales and marketing. He suggests simplistic ROI models risk undermining credibility.He concludes that demand remains strong and success will depend on adapting quickly, building new capabilities, and maintaining a culture that embraces continuous change.

#282 RWS CEO Ben Faes on Why They Partnered with Cohere

Ben Faes, CEO of RWS, joins SlatorPod to talk about the markets’ perceptions of LSIs, the company’s AI strategy, and how RWS is repositioning itself for long-term growth.Ben positions RWS as a technology-led partner helping enterprises operate globally, from enabling multilingual communication to protecting intellectual property and improving market understanding.The CEO highlights the rapid acceleration of innovation and the democratization of AI, where individuals and companies can now build and deploy solutions at unprecedented speed. He argues that the real opportunity lies in using these capabilities more effectively, rather than applying them to low-value tasks.He describes the partnership with Cohere as a fundamental shift, with RWS integrating Cohere’s models into its Language Weaver Pro platform, moving beyond traditional, segment-based translation toward context-aware, LLM-driven solutions.Beyond translation, Ben sees strong growth in AI data services, especially in areas like cultural intelligence and multimodal training, where human expertise remains critical. Internally, RWS has reorganized into three divisions — Generate, Transform, and Protect — to better align with customer needs, buyer personas, and evolving use cases.Despite short-term uncertainty, Ben remains optimistic, noting that new AI-driven services and products account for a growing share of revenue and signal how quickly the market is evolving.

#281 What Is AI Audio Separation with AudioShake CEO Jessica Powell

Jessica Powell, CEO of AudioShake, joins SlatorPod to talk about how AI-powered audio separation is making audio more usable for both human and machine workflows, and enabling new use cases across localization, broadcasting, and media production. Jessica emphasizes that early traction came from the music industry, particularly in areas like sync licensing and remixing. However, the company’s expansion into film and television happened organically as new use cases emerged.The CEO explains that AudioShake’s core technology uses source separation to break complex audio into individual components such as dialogue, music, and sound effects. She describes how this allows users to gain precise control over audio for tasks like editing, transcription, and multilingual dubbing.In localization, Jessica highlights how separating dialogue from music-and-effects (M&E) tracks enables both traditional dubbing and AI-assisted workflows, particularly for legacy content where original stems are unavailable.Beyond localization, Jessica underscores the importance of clean audio inputs for speech recognition systems. In noisy environments like sports broadcasts or unscripted content, separating dialogue before transcription significantly improves accuracy.Jessica also reflects on the broader AI landscape, noting that the rise of generative AI has increased awareness of audio as a critical modality. However, she distinguishes AudioShake’s work as non-generative, focused on extracting structure rather than creating new content.The CEO discusses the current funding environment in the Bay Area and how the investor narrative has evolved leading up to AudioShake’s late 2025 Series A.Looking ahead, Jessica points to real-time processing and copyright-compliant audio editing as key areas of innovation, as the company continues to expand its role in media and AI ecosystems.

#280 Walmart Cuts Translation Costs, 10 LTP Growth Hacks

Daniel Sebesta joins Florian and Esther on the pod to talk about the latest language industry news, AI translation developments, and key insights from the Slator Pro Guide: Growth Hacks for Language Technology Platforms (LTPs).The trio begin with TransPerfect’s latest financial results, which reported USD 1.32 billion in revenue, up 7% year on year. They also discuss leadership changes at Straker, where founder Grant Straker stepped down as CEO after more than 25 years.Florian shares new AI-powered contextual features in Google Translate that allow users to refine translations and adjust tone or phrasing. Daniel believes these interactive capabilities aim to improve trust in AI systems by giving users more visibility and control over translation outputs.The discussion also turns to ElevenLabs and its partnership with Deutsche Telekom to embed live translation into phone calls. The integration could enable real-time multilingual conversations, summaries, and contextual assistance for telecom customers.The trio then cover Walmart’s internal AI localization initiative, where the system now translates millions of catalog items across 22 languages while reducing translation costs by about 99%.Daniel concludes by outlining the Growth Hacks Pro Guide, which explores strategies for scaling LTPs. He highlights areas such as go-to-market strategy, partnerships with language solutions integrators, enterprise sales execution, and security readiness as key drivers of scalable growth.

#279 Why Phrase Doubles Down on a Platform Strategy with CEO Georg Ell

Georg Ell, CEO of Phrase, returns to SlatorPod for round 3 to talk about how the language technology platform (LTP) is evolving amid the AI boom and the shifting dynamics in enterprise SaaS.Georg shares how Phrase has doubled down on a platform and ecosystem strategy that encourages customers to build solutions on top of the LTP’s system rather than forcing them into a closed system.The CEO addresses the broader AI narrative affecting SaaS companies and explains that investor uncertainty about long-term software value has created anxiety across the sector.Georg argues that the AI boom has triggered a “build vs buy” debate inside many enterprises, with engineering teams experimenting with internal solutions. He explains how the gap between building a demo versus running a reliable, scalable system is where most internal projects fail.Georg notes that core AI translation quality improvements seem to be plateauing, but AI continues to significantly enhance the layers surrounding translation. He highlights improvements in context handling, evaluation, automated post-editing, and orchestration that allow companies to translate more content at lower human review rates.The CEO says localization must move beyond cost reduction narratives and instead focus on business outcomes such as hiring efficiency, support performance, and revenue metrics. Georg predicts 2026 will bring more production-grade AI applications, including personalization, multimodal content, and automation across the enterprise. He believes language technology will be framed as content adaptation and delivery rather than simply translation.