Josh Miller and Christopher Antunes, Co-Founders and co-CEOs of 3Play Media, join SlatorPod to talk about the company’s trajectory as a leading language solutions integrator (LSI) in multilingual video accessibility.

The duo explains how the two met at MIT, where an early challenge from OpenCourseWare revealed that captioning thousands of technical videos was financially impossible, leading to the company’s founding, where they developed proprietary tooling, leveraged AI, and incorporated expert-in-the-loop solutions.

Josh describes how their platform evolved into a dual system supporting both customers and large-scale operations. Chris notes that the LSI now serves media and entertainment, higher education, e-learning, and corporate clients.

Chris explains that three major trends — the European Accessibility Act (EAA), advancements in voice technology, and the rise of live events — drove their expansion into global localization. 

The co-CEOs detail their dubbing journey, noting rapid learning over the last 18 months and the emergence of a big mid-tier market between high-end theatrical dubbing and low-cost AI-only output.

Josh explains how the EAA is pushing companies to prepare for large columns of multilingual captioning and audio description. He notes that interpretations of the law still vary, but major media firms are already investing to avoid disruption. 

The duo shares findings from their 2025 State of ASR Report, where they found that accuracy initially improved sharply with generative models but has now plateaued.

Looking to the future, the co-CEOs are working on shifting their model to incorporate AI-generated scores and analytics, allowing customers to decide on the level of expert intervention.

Florian and Esther discuss the language industry news of the past few weeks, reflecting on SlatorCon Remote and announcing that SlatorCon London 2026 is open for registration.

The duo touch on IMDb’s decision to recognize dubbing artists as part of new professional credit categories, explaining how this expands visibility for multilingual voice talent. They then move on to Coursera’s strategy shift and outline how its new CEO is betting on AI translation and AI dubbing to revive slowing growth. 

Florian and Esther talk about Amazon’s rollout of AI-translated Kindle eBooks, and question authors' willingness to rely on automated translation despite Amazon’s promise of fast turnarounds, in as little as 72 hours.

Florian highlights research on spatial audio improving AI live speech translation, and reflects on how clearer speaker differentiation could enhance comprehension. Although he stresses ongoing challenges in live settings, like latency and overlapping speech.

In Esther’s M&A and funding corner, healthcare AI technology startup No Barrier raises USD 2.7m, Cisco acquires EZ Dubs to enhance WebEx’s real-time speech translation capabilities, and audio AI startup AudioShake raises USD 14m. 

Florian analyzes OneMeta’s financials and notes its rapid revenue growth despite significant ongoing and limited marketing presence. Esther details the landmark UK NHS framework agreement for language services, including scope and the number of awarded vendors.

Florian concludes with updates on interpreting performances at Teleperformance and AMN Healthcare, noting mixed results.

Amir Haramaty, Co-Founder and President of aiOla, joins SlatorPod to talk about how spoken, multilingual data can transform enterprise workflows and unlock real ROI.

The Co-Founder introduces himself not as a serial entrepreneur but as a serial problem solver, focused on one core challenge: most enterprise data remains uncaptured, unstructured, and unused.

Amir emphasizes that traditional speech tech fails in real-world conditions, where accents, noise, and hyper-specific jargon dominate. He illustrates how he tackles this challenge by building workflow-specific language models that extract only the data relevant to a process.

Amir says aiOla converts speech not into text but into structured, schema-ready data, allowing organizations to automate workflows, improve compliance, and identify trends long before humans can. He explains that the company focuses on narrow processes rather than general conversation, enabling precision in niche environments.

Amir shares how aiOla routinely cuts multi-hour procedures down to minutes, drives efficiency across frontline roles, and creates previously unavailable datasets that feed enterprise intelligence. He highlights ROI examples from supermarkets, airlines, manufacturing, and automotive industries.

Amir explains that after proving aiOla’s value, he realized the fastest way to scale was through firms already embedded in enterprise digital transformation. He notes that aiOla now partners with UST, Accenture, Salesforce, and Nvidia, creating a distribution engine capable of replicating wins across thousands of clients. 

He calls this channel strategy a force multiplier that shortens sales cycles and embeds aiOla inside broader modernization initiatives. Amir adds that these partners not only bring scale but also domain expertise aiOla deliberately chose not to build in-house. 

Amir outlines future priorities, including product-led growth, speech-based coding, and speech-prompted AI agents. He predicts that agentic systems will rely heavily on high-quality spoken data, making aiOla’s role even more central.

Tom Kocmi, Researcher at Cohere, and Alon Lavie, Distinguished Career Professor at Carnegie Mellon University, join Florian and Slator language AI Research Analyst, Maria Stasimioti, on SlatorPod to talk about the state-of-the-art in AI translation and what the latest WMT25 results reveal about progress and remaining challenges.

Tom outlines how the WMT conference has become a crucial annual benchmark for assessing AI translation quality and ensuring systems are tested on fresh, demanding datasets. He notes that systems now face literary text, social-media language, ASR-noisy speech transcripts, and data selected through a difficulty-sampling algorithm. He stresses that these harder inputs expose far more system weaknesses than in previous years.

He adds that human translators also struggle as they face fatigue, time pressure, and constraints such as not being allowed to post-edit. He emphasizes that human parity claims are unreliable and highlights the need for improved human evaluation design.

Alon underscores that harder test data also challenges evaluators. He explains that segment-level scoring is now more difficult, and even human evaluators miss different subsets of errors. He highlights that automated metrics built on earlier-era training data underperformed, particularly COMET, because they absorbed their own biases.

He reports that the strongest performers in the evaluation task were reasoning-capable large language models (LLMs), either lightly prompted or submitted with elaborate evaluation-specific prompting. He notes that while these LLM-as-judge setups outperformed traditional neural metrics overall, their segment-level performance varied.

Tom points out that the translation task also revealed notable progress from smaller academic models around 9B parameters, some ranking near trillion-parameter frontier models. He sees this as a sign that competitive research is still widely accessible.

The duo concludes that they must carefully choose evaluation methods, avoid assessing models with the same metric used during training, and adopt LLM-based judging for more reliable assessments.

Nikita Agarwal, Founder of Milestone Localization, joins SlatorPod to talk about her journey founding a language solutions integrator (LSI) and launching Cavya.ai, a platform designed to streamline translation project preparation.

Nikita began Milestone Localization in 2020 after discovering the language industry while working in international sales. She was drawn to the field’s global scope and low barrier to entry. She emphasizes that sales experience played a crucial role in landing early clients and understanding the value of hiring people from within the industry. 

The founder reflects on the past 16 months as a period of intense change marked by AI disruption, client pressure on pricing, and shifting expectations. She highlights how regulated sectors like life sciences have helped stabilize the company amid volatility. She details how the LSI specializes in medical device translations and regulatory submissions across Europe.

Nikita explains that her new platform, Cavya.ai, emerged from internal needs to improve project preparation. She says the tool automates glossaries, style guides, and document analysis, reducing time and boosting consistency for small and mid-sized projects.

The founder shares her observations on India’s evolving language technology landscape, noting significant progress in AI for major Indian languages. She says increased internet access and AI-driven localization are expanding education and job opportunities across the country.

Nikita concludes that she sees the future in expanding life sciences work, refining Cavya, and developing an AI-powered QA tool. She notes that some clients are showing “AI fatigue” and returning to human-led workflows.

Thordur Arnason, Global AI GTM Lead at Capgemini Invent, joins SlatorPod to talk about how the consulting giant is embracing language AI through BabelSpeak, its new real-time AI speech translation platform.

Thordur explains that the idea emerged from Capgemini’s AI Futures Lab while researching multimodal AI. Inspired by Meta’s launch of the Seamless M4T model, the team set out to tackle the hard problem of live AI speech translation.

He notes that early pilots with DNB Bank, the Norwegian Red Cross, and the Norwegian Police tested BabelSpeak in critical situations — from refugee banking access to emergency communication.

Thordur highlights Capgemini’s partnerships with Nvidia and Telenor, saying Nvidia provides the AI hardware and models, while Telenor’s sovereign AI infrastructure ensures security, GDPR compliance, and data sovereignty.

He emphasizes that BabelSpeak’s reliability comes not just from AI models but from engineering precision, reducing latency from three seconds to under 300 milliseconds.

Thordur discusses Capgemini’s exploration of agentic AI, where autonomous systems perceive, reason, and act independently. He describes how the company built an “Agentic Workbench” to help non-technical users experiment with AI agents safely and sees BabelSpeak as a potential tool within larger agentic systems.

He concludes that Capgemini is expanding BabelSpeak into a broader suite of language tools, combining secure AI infrastructure with advanced multilingual communication for enterprise and government clients.

Florian and Esther discuss the language industry news of the week, with congratulations to Villam Language Services on its sale to InAnyLanguage. Slator served as joint exclusive advisor with Maveria Advisory, representing Villam throughout the end-to-end M&A process.

The duo turns to Perplexity’s Localization Manager job posting, which they found almost identical to OpenAI’s earlier post, down to matching structure, order, and phrasing. They question whether copying such a specific ad shows a lack of seriousness or simply reflects practicality and efficiency.

Esther and Florian talk about RWS's new leadership hires: Stephen Lamb as Chief Financial Officer and Michael Wayne as Head of Media and Entertainment. Esther outlines how the appointments strengthen RWS’s investment strategy in media localization, dubbing, and content adaptation.

Esther next mentions that Visual Data has named Maz Al-Jumaili as SVP of Worldwide Localization, to lead subtitling and dubbing operations and strengthen client partnerships.

The duo wrap up with the UK government’s bizarre energy-efficiency study, claiming AI translation is a thousand times greener than human translation. They review the flawed logic, where the report assigns human translators the entire office energy costs while excluding AI infrastructure.

Tom Bridges, CEO and Founder of CaptionHub, joins SlatorPod to talk about how a small in-house tool evolved into a global AI-powered multimedia localization platform. 

Tom began his career in post-production and visual effects before stumbling into subtitling when a client needed to localize a video into 16 languages overnight. He reveals that the disorganized workflows relying on spreadsheets inspired him to create a more efficient, centralized solution, which became CaptionHub.

Tom explains that CaptionHub has since grown from a subtitling tool into a full multimedia localization platform integrating speech recognition, machine translation, and synthetic voice. He adds that the platform’s strength lies in being AI-agnostic and offering end-to-end workflows that balance automation with human-in-the-loop processes.

Tom describes how CaptionHub’s new product suite, Timbra, enables real-time media localization and has already supported major live events. He says live captioning is technically complex but benefits from the company’s years of research into video-on-demand subtitling quality.

Tom notes that accessibility regulations like the European Accessibility Act are driving demand, while AI and language models are opening new frontiers such as lip-sync and sign-language integration. 

Tom envisions a future where speech-to-speech translation, synthetic dubbing, and real-time localization merge into seamless, scalable experiences. CaptionHub’s mission remains to make multimedia communication universally accessible and efficient through human and AI collaboration.

Florian and Esther discuss the language industry news of the week, with breaking news that DeepL is reportedly exploring an initial public offering (IPO) in the US at a potential USD 5bn valuation. This comes as DeepL now positions itself as a “global AI product and research company”. Florian also notes the launch of DeepL Marketplace and the appointment of Gonçalo Gaiolas as Chief Product Officer.

Florian opens with the first-ever Slator Award at ZHAW Zurich University of Applied Sciences, where Guy Ratnitsky won for his thesis on data security and confidentiality in AI. The program will soon be renamed MA in Multilingual Communication Management to reflect market realities.

The duo turns to Anthropic’s new Economic Index, which shows translators and interpreters make up 0.63% of Claude AI usage, while OpenAI data previously showed translation-related conversations at 4.5%. 

Florian unpacks comments from German Chancellor Friedrich Merz, who, during a visit to Spain, suggested AI could replace EU interpreters in the medium term. He explains that Spain is pushing for Catalan, Basque, and Galician to become official EU languages, but Merz cited translation workload and complexity.

Florian and Esther then run through live AI speech translation updates: Zoom’s in-house rollout, Apple’s AirPods, Google’s translation features, Microsoft’s API, and Meta’s Ray-Bans.

In Esther’s M&A corner, she reports on Bering Lab’s acquisition of Intersphere in Korea and Iyuno’s partnership with Motion Picture Solutions in the UK for a film localization pipeline. Meanwhile, Testronic secured funding to scale down in some locations while expanding in Manila as a hub for QA testing and localization.

Slator’s Senior Research Analyst Alex Edwards joins Esther and Florian on the pod to discuss ElevenLabs’ move from a pure-play language technology platform (LTP) to becoming a language solutions integrator (LSI) by adding a managed service offering.

He outlines that the LSI will now offer managed services such as dubbing, transcription, and subtitling, hiring in-house linguists and vendor managers, while charging about USD 22 per minute for dubbing.

Florian then turns to YouTube’s rollout of multi-language audio tracks, which allows some creators to upload high-quality audio directly to videos and opens major opportunities for AI dubbing providers. 

The discussion shifts to OpenAI’s research on ChatGPT usage, reporting that translation accounted for 4.5% of more than a million sampled conversations, underscoring massive global demand for AI translation.

Esther highlights Microsoft’s launch of its Live Interpreter API, which promises real-time speech translation with “human interpreter level latency”. Esther also details Mistral’s USD 2bn funding to advance European AI capabilities, allowing them to compete with US and Chinese AI giants. Esther closes by reporting on WIPO’s new Korean-English post-editing tender.

Florian and Esther discuss the language industry news of the past few weeks, beginning with a recap of SlatorCon Silicon Valley 2025, where the duo noted strong localization buyer and user turnout, and tech-focused discussions across presentations and panels.

One key highlight was Cohere’s well-timed launch of Command A Translate, which allowed Kelly Marchisio to share details on building multilingual LLMs. Esther notes that Cohere’s multilingual models focus on high-quality coverage of about 20 languages rather than attempting hundreds.

Florian turns to the Apertus launch in Switzerland, where EPFL, ETH Zurich, and the Swiss Supercomputing Centre released a multilingual model trained on over 15 trillion tokens and covering more than 1,000 languages, including Swiss German and Romansh.

Esther reveals that Middlebury Institute will phase out its graduate translation and interpretation programs by 2027, marking the loss of a key training ground.

Esther reports on TransPerfect’s acquisition of Unbabel, with plans to integrate its AI tools, such as TowerLLM and EuroVLM, into GlobalLink, while CEO Vasco Pedro will stay briefly during the transition. 

Florian outlines Apple’s launch of AirPod Pro 3 with live AI translation and Google’s new Gemini-powered updates for AI live speech translation.

Esther concludes with the Inc. 5000 rankings, highlighting 11 language industry companies. She highlights Propio, Boostlingo, and CQ Fluency as repeat entrants, with Propio topping the list but also announcing job cuts following its acquisition of CyraCom.

Dipak Patel, CEO of GLOBO, joins SlatorPod to talk about his journey into language services and the challenges and opportunities of integrating AI into healthcare communication.

Dipak explains that his career began in consulting and private equity, but a personal experience with his mother’s healthcare highlighted the importance of interpretation services and led him to GLOBO.

The CEO emphasizes that since 2020, GLOBO has doubled down on healthcare, embraced AI and large language models, and addressed the mounting pressures of clinician shortages and aging populations. 

Dipak gives an overview of GLOBO’s platforms: HQ provides backend data and reporting, Connect enables access to interpreters through mobile devices, and KAI is the company’s AI interpreter, which is undergoing pilots across US hospitals.

Dipak cautions that AI cannot replace expert interpreters in all situations as interpreters serve as more than simple conduits; they clarify meaning, act as cultural brokers, and advocate for patients. He believes the near-term role of AI is filling gaps in the patient journey where interpretation currently does not happen.

Dipak details how GLOBO is using AI to monitor interpreter quality in real time, checking professionalism, background noise, and accuracy. He stresses that security, data protection, and careful testing are crucial to AI adoption in healthcare.

Dipak reflects on the growth of GLOBO, attributing it to a strong team and relentless focus on innovation. He concludes that while AI will play a bigger role in the next decades, the key lies in balancing it with human expertise.

Gayatri Shahane, Founder and CEO of early-stage startup Naitiv, joins SlatorPod to talk about her entrepreneurial journey and building a conversational AI tool for business communication.

Gayatri describes how Naitiv’s conversational AI agent is built as a desktop app to manage latency and audio challenges in live interpretation. She explains that it supports different conversation modes for casual and professional contexts, with a voice orchestration engine developed to handle turn-taking, speaker overlaps, and multiple languages.

The Founder recalls testing the technology in live Discord language-learning channels, where she conversed with Spanish, Korean, and Japanese speakers who often did not realize they were speaking with an AI.

She highlights that her early adopters include B2B companies expanding into Asia, Latin America, and Europe, using the platform for sales, onboarding, and critical client meetings. 

Gayatri acknowledges the competitive market in real-time AI interpreting, but believes there is space for smaller, more specialized tools. She adds that marketing has so far been founder-led and organic.

Gayatri concludes by sharing her plans to raise a pre-seed round and evolve Naitiv beyond meetings into a full AI agent.

Rick Woyde, Co-Founder of Pairaphrase, joins SlatorPod to talk about his entrepreneurial journey co-founding a language technology platform (LTP) focused on simplicity and accessibility.

Rick describes identifying early adoption of Google Translate among businesses and spotting a gap for a platform that served both non-technical users and professionals without the complexity of traditional LTP tools.

The Co-Founder highlights that Pairaphrase now serves diverse clients, from US schools translating educational documents to corporations managing multilingual content, with SaaS-based offerings and annual subscriptions.

He outlines how the AI boom has expanded the market for translation software and how Pairaphrase integrates generative AI to enable file translation via ChatGPT, custom GPT models, and prompt-based original content creation. 

Rick emphasizes the growing importance of language variety, the flexibility of LLMs, and the ability to quickly meet niche language requests. He also discusses the challenge of adding features without overcomplicating the UI, prioritizing automation of complex tasks in the background.

The Co-Founder shares how Pairaphrase grew largely under the radar through SEO and content marketing before expanding its marketing team. He acknowledges challenges from changes in Google’s search landscape and notes growing referrals from AI tools like ChatGPT.

Rick closes by previewing upcoming developments, including a proprietary GPT designed to deliver high-quality, customizable translations and the launch of a mobile real-time speech translation app.

Slator’s Head of Research Anna Wyndham joins Florian on the pod to discuss Microsoft’s research paper “Working with AI: Measuring the Occupational Implications of Generative AI”, a study that stirred significant debate across social media.

The paper, based on 200,000 anonymized Microsoft Copilot interactions, aims to understand what tasks people ask AI to perform and how effectively those tasks are completed. Pairing this with the US O*NET database of occupational tasks, researchers created an "AI applicability score" to assess overlap between AI-capable tasks and real-world job functions.

Anna emphasizes that the researchers distinguish between AI performing individual tasks and full jobs. Even the most affected roles, like interpreters and translators, show only partial overlap, around 50%, with activities AI can complete.

Florian and Anna stress that the research does not claim AI will replace top-ranked occupations. Rather, it shows where AI is most often helpful, with knowledge-based activities like writing, summarizing, and gathering information topping the list. 

The Microsoft researchers also acknowledge key limitations. For example, jobs are more than bundles of disconnected tasks; they involve context, judgment, and synthesis, often referred to as the "glue" that AI lacks. Additionally, Anna points out that Copilot’s integration into tools used by knowledge workers may bias the results in its favor.

Ultimately, the duo agree the paper validates what’s already known: AI is helpful for language-related tasks, but not transformational enough yet to supplant the people who perform them.

Martina Russo, CEO of The Action Sports Translator (TAST), joins SlatorPod to talk about her journey from being a multilingual outdoor sports enthusiast to leading a language solutions integrator dedicated exclusively to action and outdoor sports.

Martina describes how each action sport has unique subcultures and terminology, from mountain biking’s multiple disciplines to climbing’s variety of techniques and jargon. Even within the same sport, regional language differences present challenges.

For Martina, authentic translation in this industry means more than linguistic quality; it requires a translator who genuinely lives and breathes the sport to capture its culture, humor, and insider tone. She emphasizes the difficulty in sourcing linguists who are both trained translators and passionate sports practitioners, especially for rare languages or specific verticals.

The CEO shares how TAST deploys AI internally for operational efficiency and leverages it in content creation and localization, though she’s cautious about fully replacing human experts. Product copy and FAQs are areas where AI is more applicable, but the authentic, emotional connection critical to sports brands often requires a human touch.

Despite industry challenges amid fluctuating demand, TAST has been experiencing strong growth, even surpassing previous expectations. Martina attributes this success to unwavering niche focus, technological adaptation, and a company culture deeply immersed in the sports it serves.

Looking ahead, Martina remains committed to investing in developing AI solutions, hiring for roles in that department, and staying on top of trends in the outdoor sports and organization industries.

Florian and Esther discuss the language industry news of the week, including the newly released Slator 2025 Language AI 50 Under 50, showcasing fifty of the most innovative and fast-growing language AI startups founded within the past fifty months.

The duo explain how Slator sifted through hundreds of companies, assessing innovation, practical solutions to real buyer problems, and strong market positioning. The final fifty span five categories: multilingual video and audio, live speech translation, transcription and captions, translation and text generation, and accessibility.

The conversation then moves on to language AI and services in the public sector. Esther talks about a new language AI tool, DiploIA, developed and deployed by the French Government for diplomatic agents in sensitive missions.

Turning to the US, Esther reports that SOSi secured a significant USD 260m language services contract with the US Drug Enforcement Administration. Meanwhile, the US Defense Health Agency is looking for providers to deliver large volumes of translation and interpreting services.

Esther also revisits the major acquisition of CyraCom by Propio, calling it one of 2025’s biggest language industry deals. Propio now joins forces with CyraCom’s established presence in healthcare and legal interpreting, creating a combined entity with revenues exceeding half a billion dollars and positioning them strongly in the US interpreting market.

Florian questions AI voice startup ElevenLabs’ plans for an IPO within five years. He then wraps up the pod by exploring large reasoning models (LRMs) and their mixed performance in AI translation. While LRMs outperform traditional LLMs in complex, open-domain translation tasks, research indicates they remain prone to significant weaknesses.

Florian and Esther catch up on a few weeks’ worth of language industry news with a surge of developments in speech translation. Apple’s on-device translation debuts in apps like iMessage and FaceTime, and OpenAI enhances ChatGPT‘s Advanced Voice Mode with more human-like interactions and real-time translation.

Florian unpacks YouTube’s broad rollout of AI dubbing for 80 million creators in 20 languages, where he trials German and finds robotic voices, bad translations, and no editing options, leaving much to be desired.

Esther talks about RWS acquiring Papercup’s IP, aiming to embed AI dubbing into Trados and significantly boost RWS’s capabilities and market reach. RWS’s half-year financials also show slight revenue drops but rising AI-driven revenue, alongside a reorganization into three divisions: Generate, Transform, and Protect

The duo analyzes Meta’s USD 14bn investment for a 49% stake in Scale AI, which raises concerns from other tech giants uncomfortable with a major competitor owning a key data-labeling supplier. They note opportunities arising for competitors like Labelbox, RWS’s TrainAI, Welo Data, and many other LSIs as clients reconsider vendor relationships in light of Meta’s involvement.

In Esther's M&A corner, Propio acquires CyraCom to become a half-billion-dollar language solutions integrator, DigitalTolk buys 24translate to expand into the DACH region, and Powerling boosts its life sciences footprint with the acquisition of Idem.

Rounding out the episode are leadership changes, with XTM appointing Rob Finney as CMO and CQ Fluency naming Tameeka Smith as CEO following the long tenure of Elisabete Miranda.

Davit Baghdasaryan, Co-Founder & CEO of Krisp, joins SlatorPod to talk about the platform’s journey from a noise cancellation tool to a comprehensive voice productivity solution.

Originally built to eliminate background noise during calls, Krisp has expanded into real-time accent conversion, speech translation, agent assistance, and note-taking — technologies being rapidly adopted in enterprise environments.

The company’s accent conversion is now deployed by tens of thousands of call center agents, significantly improving metrics like customer satisfaction and call handling time.

Davit details Krisp’s live AI speech translation feature which uses a multi-step pipeline of speech-to-text, text translation, and text-to-speech. The majority of use cases are in high-resource language pairs such as English, Spanish, French, and German, although Davit recognizes the importance of expanding to lower-resource languages.

He shares how Krisp is also seeing increased demand in human-to-AI voice communication. AI voice agents are highly sensitive to background noise, which disrupts turn-taking and response accuracy. Krisp’s noise isolation tech plays a foundational role in enabling smoother voice AI interactions, with billions of minutes processed monthly by major AI labs and startups.

The CEO discusses LLMs' impact, noting how they enable advanced features like note-taking, call summaries, and real-time agent guidance. He sees Krisp as a platform combining proprietary technologies with third-party AI to serve both B2B and B2C markets.

Davit advises startups to explore the vast and still underdeveloped voice AI landscape, noting the current era is ripe for innovation due to AI advancements. He highlights Krisp’s roadmap priorities: expanding accent packs, refining voice translation, and building more AI Agent Assist tools focused on voice workflows.

Stefaan van der Jeught, Professor of EU Constitutional Law at Vrije Universiteit Brussel, and a Press Officer at the Court of Justice of the European Union, joins SlatorPod to talk about the complex relationship between language and law in the EU.

Stefaan outlines the historical evolution of EU language policy, from French-only founding treaties to the gradual inclusion of all member state languages. Despite formal equality, institutions largely define their own internal language regimes, leading to fragmented and often English-centric practices. 

Stefaan’s book EU Language Law, now in its second edition, examines these issues in depth. Updated with new case law, legislation, and developments in AI and governance, it includes a 10-point roadmap for reform. Stefaan advocates for greater transparency, legal protection of linguistic diversity, and a constitutional debate on the role of language in EU integration.

AI, Stefaan believes, is a tool that can enhance multilingual access and consistency across EU communications. However, he cautions against using AI as a cost-cutting measure that replaces linguistic expertise. Instead, AI should serve as a support tool, with human revision, especially in legal contexts.

On regional languages like Catalan, Basque, and Galician, Stefaan notes they face legal hurdles at the EU level because they lack full legislative status in their home countries. He argues for a more transparent and constitutional debate on language policy, drawing inspiration from multilingual countries like Switzerland and Belgium.

Stefaan concludes by advising universities to train future legal linguists by going beyond technical instruction to foster critical thinking, comparative law expertise, and cultural literacy.

Tom Elias Hanna, COO of Hanna Interpreting Services (Hanna), joins SlatorPod to talk about how a family-run interpreting initiative grew into a national language solutions integrator (LSI).

Tom explained that the company was born out of necessity during an influx of Arabic-speaking refugees in San Diego, with his mother providing interpretation and him leveraging his legal background to establish a compliant, scalable business that now serves healthcare, government, education, and social service sectors across California.

Tom described how their inclusion-focused work led to partnerships like one with San Diego FC, where they provide ASL at every home game. He emphasized that while AI holds potential in sign language interpretation, it must evolve with and for the deaf community to be truly effective, due to cultural, emotional, and experiential nuances that current technologies cannot replicate.

On-site language interpretation remains the core service, especially across healthcare, education, and social services. Though remote interpreting and AI are on the rise, Tom emphasizes the irreplaceable value of human interpreters, particularly in high-stakes, emotionally nuanced settings like hospitals.

Tom explained that their recent rebrand emphasizes both human connection — central to their on-site interpreting services — and technological growth.

Initially, without a sales team, Hanna grew through referrals, client satisfaction, and high service quality. Only after COVID did Tom begin to formalize a sales strategy and identify account management as a natural extension of their client-first approach.

Tom expressed that despite considerable internal and industry-wide discussions, the Trump Executive Order designating English as the only official language of the US had no tangible effect on Hanna, so far. He noted that no clients inquired about it or changed their behavior.

Looking ahead, Tom aims to scale geographically, explore strategic acquisitions, and develop proprietary technologies to improve experiences for clients, staff, and linguists alike.

Florian and Esther welcome Slator’s Anna Wyndham and Alex Edwards to SlatorPod to explain the rationale behind the new industry framework introduced in the Slator 2025 Language Industry Market Report.

Drawing from the flagship report and echoing the buzz of SlatorCon London, the team explains why the traditional labels, Language Service Providers (LSPs) and Translation Management Systems (TMSs), no longer capture the scope and complexity of the evolving market. Instead, Slator has introduced two new terms: Language Solutions Integrators (LSIs) and Language Technology Platforms (LTPs).

Anna defines LTPs as pure-play technology providers that develop language tools, applications, orchestration platforms, and AI models. LSIs, she explains, are organizations whose core offering is to deliver fit-for-purpose multilingual content solutions by integrating language technology and AI with human experts as part of a fully managed solution.

Esther confirms early advisory adoption of the terms, noting investor interest in clearer tech-service distinctions. Alex adds that automatic dubbing startups tend to fit LTPs better than LSPs, as they often operate self-serve AI platforms.

Anna clarifies that big tech players like OpenAI and Google are excluded from the market sizing as they are foundational enablers, not language-focused businesses. The team also discusses why the term “AI” was excluded from the new categories as it may become as ubiquitous as “Cloud”.

To close, Anna points out that LSIs currently capture the bigger portion of the total addressable market (TAM). The team sees a strong demand for expert-in-the-loop services and growing LTP–LSI partnerships.

In a SlatorPod first, four guests — Scott Cooper, CEO of Language Services Associates (LSA), Pablo Tercero, COO of LSA, Jerry Song, CEO of Lingolet, and Edward Varela, VP of Business Development at Lingolet — shared their insights into a newly forged partnership.

Scott explained that the decision to partner instead of building an in-house AI solution allowed LSA to stay focused on its core strengths while leveraging Lingolet’s technical edge. The alliance goes beyond a vendor agreement, with LSA taking an equity stake in Lingolet, anchoring the relationship in shared strategy and long-term commitment. 

For Jerry and Edward, the partnership is a natural progression, rooted in their deep knowledge of both software development and the language services market.

In a standout use case, the two companies helped a Major League Soccer team enable multilingual, AI-assisted communication in coaching sessions — bridging language gaps in real time for international players.

On the tech front, Jerry and Edward explained that Lingolet doesn’t build large language models from scratch but instead acts as an orchestrator, offering clients the ability to customize and deploy AI tools within secure, dedicated environments. 

Pablo underscored LSA's HIPAA and PCI compliance, as security, compliance, and privacy are essential pillars, especially in regulated sectors like healthcare.

Looking ahead, LSA and Lingolet are preparing to offer hybrid solutions where AI can bridge the gap during interpreter unavailability, even for brief moments, potentially transforming session wait times. 

Their roadmap includes broader language coverage, deeper integration with healthcare platforms, and innovative pricing models that will reshape how interpretation services are sold and scaled.

Rong Yan, CTO of HeyGen, joins SlatorPod to recount the company’s transformation from a Metaverse-focused startup to leading the emerging field of AI video generation.

Rong recounts HeyGen’s beginnings and the pivot to its current avatar model, which saw ARR go from zero to USD 1m within six months.

Rong attributes HeyGen’s success to its emphasis on three key elements: quality, consistency, and controllability. The company’s newest model, Avatar IV, enables full-body video generation with natural gestures, synchronized audio, and emotion to speech.

While some of the platform’s growth has been viral, Rong believes sustained success comes from building something users truly value, with a focus on pushing video quality from 70% to 95%.

The platform extends beyond avatars, offering translation, voice cloning, and real-time interactivity. Its dynamic duration feature adjusts translated speech to fit original video timing, preserving realism. Rather than build everything from scratch, HeyGen integrates external models with its own orchestration and user data, optimizing output across languages and contexts.

Rong emphasized that HeyGen’s long-term vision is not entertainment or Hollywood, but helping everyday professionals, especially marketers and educators, who lack traditional video production skills.

Looking ahead, Rong sees video agents, tools that generate complete videos from simple prompts, as the next frontier, driving accessibility and transforming storytelling through AI.

Véronique Özkaya, Co-CEO of DATAmundi, returns to SlatorPod for round 2 to talk about the company’s strategic rebrand and how it is positioning itself as a key player in the data-for-AI space.

Véronique details her journey to leading DATAmundi, formerly known as Summa Linguae, where she now drives a strategic shift from traditional language services to AI-focused data enablement.

The Co-CEO explains that their LSP background makes them well-suited to offer fine-tuning services for AI, especially in multilingual and domain-specific contexts. However, she cautions that language expertise alone isn’t enough; deep tech infrastructure, data science capabilities, and the ability to quickly build custom workflows are also essential.

While many companies still rely on crowd-sourced, basic annotation, DATAmundi targets higher-complexity projects requiring domain experts and linguists. Véronique notes the market for data-for-AI is growing significantly faster than traditional LSP work and sees a second wave of demand from enterprises needing to adapt pre-trained models.

Véronique highlights data scarcity, hallucination, and bias as core AI challenges that DATAmundi tackles through technical solutions and expert guidance, helping enterprises as they face pressure to implement AI despite legacy systems and unclear strategies.

Looking ahead, DATAmundi plans to expand its consultative services through further acquisitions, focusing not on tech per se, but on organizations that deepen its expertise in data application and AI deployment.