SlatorPod

Florian and Esther discuss the language industry news of the past few weeks, starting with RWS’s proposed acquisition of Acolad and what the deal means for consolidation among the largest language solutions integrators (LSIs). 
Esther rounds up further M&A activity, including t’works acquiring SwissGlobal, Alfatrad buying Lexic Language Solutions, Alpha CRC acquiring PureFluent, Magna Legal Services merging with Naegeli Deposition and Trial, R&A Translators buying Viva Translations, and Contents acquiring Balio.
Esther and Florian examine Anthropic’s introduction of invisible watermarks for Claude-generated text in response to the EU AI Act. Florian questions how meaningful AI-content labeling will remain as AI becomes embedded in content creation and translation, while Esther points to transparency as the regulation’s underlying objective.
Florian reviews ZOO Digital’s declining revenue, improving profitability, growing use of AI, and shift toward faster localization services and more fulfillment in India.
The duo talks about how AI skills are increasingly appearing in language roles at organizations including NATO, the ICC, WIPO, Interpol, FIFA, and the IMF. Esther contrasts this with a more traditional language-access role in New York and OpenAI’s continued hiring of localization specialists to oversee AI-assisted workflows.
Finally, Florian highlights continued investment in voice AI, with funding rounds for Fish Audio, Smallest AI, Omilia, and Gradium underscoring how crowded the speech technology market has become.

Artur Nowakowski, Co-founder and CTO of Laniqo, joins SlatorPod to talk about the language technology platform’s (LTP) origins, business model, and research-driven approach to AI translation.
Artur shares that Laniqo emerged from machine translation research at Adam Mickiewicz University after his team won a WMT 2022 shared task, attracting PONS Langenscheidt, which became the company’s main investor and helped commercialize the university’s technology.
Laniqo initially developed its own neural machine translation models but shifted toward open-source large language models as their translation capabilities improved. According to Artur, controlling and adapting these models remains essential for domain-specific use cases and lower-resource language pairs.
He highlights Laniqo’s work with Central and Eastern European ecommerce platform Allegro, where the LTP supports the translation of hundreds of millions of product offers. Key challenges include scalability, cost control, terminology, limited source context, and detecting critical errors across volumes that human linguists cannot review manually.
Laniqo is also developing quality estimation tools that identify error spans, assign MQM categories, and suggest corrections. Its recently published ForMaT dataset supports research into PDF translation that preserves document layouts without relying on conversion to Microsoft Word.
Looking ahead, Artur outlines how Laniqo plans to expand beyond text translation into voice, images, and broader language AI applications, while continuing to prioritize privacy and deeper domain adaptation.

Sean Hopwood, Founder and CEO of Day Translations, joins SlatorPod to talk about building a global language solutions integrator (LSI) over the past 20 years, adapting to AI, and why a passion for languages continues to shape the LSI's strategy.
Sean reflects on how his entrepreneurial mindset and fascination with languages led him to launch Day Translations, which has grown from handling small community projects into serving enterprise, legal, medical, and government clients while remaining bootstrapped.
He explains why human expertise remains central as the LSI adopts AI across its workflows, develops its own large language model for enterprise and government procurement, and plans to commercialize these capabilities while continuing to invest in technology.
He discusses the DayInterpreting app, which integrates with Zoom and Microsoft Teams, supports rapid interpreter connections, and is already prepared for AI interpreting when customers require it.
He argues that constant learning, business growth, and technological adaptation are essential for long-term success, while also stressing that translation plays a vital role in preserving cultures and protecting linguistic diversity.
He concludes by outlining plans to expand the interpreting platform, strengthen the LSI's B2B focus, secure additional compliance certifications, and continue combining human expertise with AI-powered language solutions.

Florian and Esther discuss the language industry news of the past couple of weeks, beginning with the newly released 2026 Slator Language AI 50 Under 50, which tracks emerging startups less than 50 months old. 
The duo observe how this year’s cohort reflects a shift from standalone language technologies toward AI solutions built around complete business workflows.
They also highlight seven trends, including the rise of agentic AI, AI-first language solutions integrators, specialist sign language startups, and the growing importance of proprietary customer data as a competitive advantage.
Florian covers a stream of language AI announcements from Google, Apple, and Anthropic as the platforms continue to expand their multilingual capabilities.
Esther recaps recent investment activity, with Rylo's USD 85m funding round for AI solutions serving deaf users, Dell Technologies Capital's USD 50m investment in voice AI startup Bland, and Gridly's USD 1.5m raise to add agentic AI capabilities to its content management platform.
Esther concludes with her M&A corner, where Powerling acquires French language solutions integrator Atlantique Traduction and Sweden-based DigitalTolk expands into Switzerland through its acquisition of legal translation specialist Hieronymus.

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.