SlatorPod

Florian and Esther discuss what mattered in language solutions and AI over the past few weeks, including key takeaways from SlatorCon San Francisco 2026, where AI ran through discussions across enterprise localization, voice AI, interpreting, data-for-AI, media localization, and venture capital.
Florian covers Smartling’s majority investment from Vitruvian Partners as a positive development after a quieter period for language-related deals. He notes that Smartling plans to use the backing to expand AI translation and agentic localization, accelerate global growth, and pursue acquisitions.
Florian examines early translation benchmarks for OpenAI’s latest model, GPT-6 Astra. He cites sources that find Astra performing well in multilingual performance but still shows some weaknesses on difficult translation tasks. He argues that expert oversight remains important for critical use cases.
Esther breaks down Appen’s first-half results, highlighting strong growth in China driven partly by generative AI projects alongside continued pressure in its global business. She also looks at AI-Media’s continued shift from captioning services toward recurring technology and SaaS revenue.
Florian turns to AMN Healthcare’s language services business, where interpreting volumes were flat, and pricing pressure weighed on revenue. He also addresses Straker’s financial difficulties following the discovery of roughly USD 5m in misappropriated funds.

Dmitrii Sandzhiev and Iurii Agafonov, two of the Co-Founders of NCSpeech, join SlatorPod to talk about building speech AI datasets in emerging markets, scaling data collection through superapps, and addressing the quality and infrastructure challenges behind voice AI.
Dmitrii explains that NCSpeech turns idle time in superapps into AI training data by rewarding drivers, riders, and passengers for completing data collection tasks. The company connects AI labs, enterprise R&D teams, and sovereign AI initiatives with real-world audio, image, and video data collected through the platform’s partners.
Dmitrii sees particularly strong demand for speech datasets in emerging markets, where languages, dialects, and code-switching remain underrepresented in training data. In Malaysia, for example, speakers frequently switch between Malay, English, Mandarin, and local dialects.
Iurii highlights the technical challenges behind producing training-ready datasets, including controlling recording conditions, verifying speaker consistency, detecting synthetic submissions, managing local data storage requirements, and processing large volumes of audio.
Alongside collecting data on demand, NCSpeech is building reusable dataset libraries and developing its own models. Dmitrii shares how its Kazakh speech recognition model now outperforms available open solutions, demonstrating its technical capabilities and attracting potential customers.
Looking ahead, Dmitrii and Iurii discuss NCSpeech plans to expand into more countries and apps, secure longer-term data customers, strengthen their US presence, and raise a seed round.

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.