SlatorPod

Slator's Anna Wyndham joins Florian on the pod to discuss key highlights from the Slator Data-for-AI Market Report, which sizes the global market at USD 9.3bn and examines the ecosystem supplying the data needed to train, adapt, align, evaluate, and deploy AI systems.
Anna explains how the market has evolved far beyond traditional data labeling. While annotation and large-scale training data remain important, she argues that the market’s focus has shifted toward helping organizations deploy AI safely and effectively in real-world settings.
Anna highlights the growing importance of “deployment data”, data used to adapt models for specific domains, align behavior with policies, conduct adversarial testing, and evaluate performance. She notes that these activities increasingly rely on subject-matter experts, creating demand for professionals such as physicians, lawyers, engineers, and financial specialists.
The discussion also explores how frontier AI labs, enterprises, and sovereign AI initiatives are driving demand. Anna shares that buyers increasingly need trusted providers capable of sourcing expert talent, scaling rapidly, and maintaining rigorous governance around data provenance and quality.
For language solutions integrators (LSIs), Anna sees both opportunity and challenge. Existing strengths in multilingual operations and workforce management provide a natural advantage, but success requires new capabilities, including expertise in machine learning workflows and AI evaluation.

Florian and Esther discuss the language industry news of the past few weeks, beginning with a recap of SlatorCon London, which attracted a record 250 attendees. 
They highlight growing interest in language AI, startup innovation, and research, as well as a broader shift in industry sentiment toward viewing LSIs and LTPs as integral parts of the AI economy rather than businesses being disrupted from the outside.
Drawing on Slator’s newly released market report, Florian shares that the total addressable market for language solutions and AI reached USD 30.85bn in 2025, declining 2.7% year on year. Traditional LSIs saw a steeper 5.1% decline, while LTPs grew nearly 20%.
The duo also examine the wider AI landscape, discussing massive funding rounds and IPO plans at Anthropic and OpenAI. Florian argues that these developments create challenges for LTPs seeking defensible market positions, citing OpenAI’s launch of real-time speech translation shortly after DeepL announced an expanded focus on voice translation. 
On company news, Florian and Esther review the bankruptcy of voice AI startup Lovo following legal disputes over voice rights and data usage, as well as the financial difficulties facing transcription specialist VIQ Solutions.
Esther closes with an overview of recent M&A activity, including acquisitions by TransPerfect, RWS, and The Translation People, alongside the formation of Germany’s new IMK Group. She also notes growing consolidation in the voice AI sector and highlights a recent funding round for Japanese AI translation startup Yellow Blue.

Sharath Narayana, CEO and Co-Founder of Sanas, joins SlatorPod to talk about the evolution of real-time speech AI, the rise of accent harmonization, and why voice will become the next major enterprise interface.
Sharath traces his journey from engineer to entrepreneur, including the founding of Observe.AI before launching Sanas alongside Stanford researchers focused on solving low-latency speech processing.
The CEO explains that Sanas initially operated as a speech lab focused on improving human understanding in conversations. The company developed multiple algorithms covering noise cancellation, speech enhancement, accent harmonization, and language translation before discovering that enterprises were most willing to pay for accent-related technology.
Sharath emphasizes that Sanas’ accent technology is not designed to erase identity, but to improve clarity and reduce friction in customer interactions. He says enterprises, especially contact centers, adopted the technology to improve first-call experiences and reduce mistrust between agents and customers.
He also discusses Sanas’ focus on on-device AI infrastructure rather than cloud-only deployments, where running speech AI locally improves latency, protects data sovereignty, and lowers compute costs.
Looking ahead, Sharath says Sanas is preparing broader launches for real-time language translation, universal accent translation, and developer SDKs that will allow third parties to build voice applications on top of the Sanas platform.

Florian and Esther discuss the language industry news of the past few weeks and Slator’s newly launched website, which reflects a clearer positioning around research, advisory, consulting, events, and market intelligence.
The duo breaks down the 2026 Slator Index, highlighting that while revenues appear to have grown, this does not signal real market expansion. Instead, growth is concentrated among a few large players, often driven by acquisitions, while many companies report declining revenues.
Florian touches on the RWS–Cohere strategic partnership, with RWS strengthening its technology stack by integrating advanced AI translation, while Cohere gains enterprise distribution. The move reflects a broader trend of companies recognizing they cannot build everything in-house.
Off the back of Slator’s Data-for-AI Market Report, Florian sees AI data services as a major growth opportunity. He explains that the industry’s bottleneck has shifted from building models to making them usable in real-world settings. Esther notes growing interest from companies exploring acquisitions and investments in this space.
Esther wraps things up by talking through recent M&A and funding deals, including Star7’s private equity buyout, GlobalComix’s expansion into manga localization with the acquisition of INKR, and VoiceLine’s EUR 10m funding round in voice AI.

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.