The initiative was selected under the EuroHPC AI Factory Large Scale call recognizing its potential to advance Europe’s leadership in multilingual artificial intelligence.

At the heart of this initiative is a mission to build strategic autonomy for Europe in AI development. By generating high-quality, ethically sourced synthetic data, it addresses a long-standing gap in linguistic representation, in particular for low-resource and minority languages.

André Martins, Chief Scientific Officer at Unbabel and EuroLLM project co-lead said:

“By joining forces through EuroLLM and OpenEuroLLM, we’re bringing together the research strength and open-source ethos needed to tackle one of Europe’s biggest AI challenges: linguistic inclusion at scale. This project is about ensuring Europe owns its language data, reflects its cultural diversity, and sets its own standards in responsible AI development.”

The GPU allocation will power the MultiSynt approach, a key component of the project which seeks to address one of the most persistent bottlenecks in multilingual LLM development: the lack of high-quality pre-training data.

“This is an important step in securing large enough computing power to build the OpenEuroLLM’s family of open LLMs. I am also glad that this has been done in collaboration with the experienced team from the EuroLLM project. The goal of this subproject is to explore multilingual synthetic data creation and evaluate their use in order to reach a higher common goal: building high-quality multilingual LLMs for all European languages and beyond.” – notes Jan Hajic, Charles University, coordinator of the OpenEuroLLM project.

While most synthetic data generation for large language models to date has focused on English, MultiSynt will create the first comprehensive multilingual synthetic dataset designed specifically for pre-training. By leveraging generative models to enhance and diversify existing content, it will support the broader aims of EuroLLM and OpenEuroLLM: building open-source, culturally grounded, and linguistically diverse AI for Europe.

This methodology will support linguistic diversity, open access, and data quality and aligns with the wider objectives of the European Commission’s Digital Decade and the AI Act.

The awarded 3 million hours reflect a strong endorsement of the project’s technical merit and strategic value.

The initiative will be executed through phased releases of the synthetic dataset.

****ENDS****

About EuroLLM
The EuroLLM project includes Unbabel, Instituto Superior Técnico, the University of Edinburgh, Instituto de Telecomunicações, Université Paris-Saclay, Aveni, Sorbonne University, Naver Labs, and the University of Amsterdam. Together they created EuroLLM-9B, a multilingual AI model supporting all 24 official EU languages. Developed with support from Horizon Europe, the European Research Council, and EuroHPC, this open-source LLM aims to enhance Europe’s digital sovereignty and foster AI innovation. 

About OpenEuroLLM

Bringing together 20 of Europe’s leading AI companies, research institutions and EuroHPC centres, the OpenEuroLLM project is creating a new generation of open source large language models for European languages. Co-funded by the European Union’s Digital Europe Programme, the project is laying the foundations for AI infrastructure that will enhance competitiveness, resilience, and digital sovereignty.

About EuroHPC
The European High Performance Computing Joint Undertaking (EuroHPC JU) is a joint initiative between the EU, European countries, and private partners to develop a world-class supercomputing ecosystem in Europe.

Media Contacts:

For more information or interview requests, please do not hesitate to reach out to our media contacts below:

• Unbabel: [email protected]

The post EuroLLM and OpenEuroLLM Secure Supercomputing Power to Build a Multilingual Synthetic AI Dataset for Europe appeared first on Unbabel.

Why We Built Translator Copilot

Translators at Unbabel receive instructions in two ways:

• General instructions defined at the workflow level (e.g., formality or formatting preferences)
• Project-specific instructions that apply to particular files or content (e.g., “Do not translate brand names”)

These appear in the CAT tool and are essential for maintaining accuracy and brand consistency. But under tight deadlines or with complex guidance, it’s possible for these instructions to be missed.

That’s where Translator Copilot comes in. It was created to close that gap by providing automatic, real-time support. It checks compliance with instructions and flags any issues as the translator works. In addition to instruction checks, it also highlights grammar issues, omissions, or incorrect terminology, all as part of a seamless workflow.

How Translator Copilot Helps

The feature is designed to deliver value in three core areas:

• Improved compliance: Reduces risk of missed instructions
• Higher translation quality: Flags potential issues early
• Reduced cost and rework: Minimizes the need for manual revisions

Together, these benefits make Translator Copilot an essential tool for quality-conscious translation teams.

From Idea to Integration: How We Built It

We began in a controlled playground environment, testing whether LLMs could reliably assess instruction compliance using varied prompts and models. Once we identified the best-performing setup, we integrated it into Polyglot, our internal translator platform.

But identifying a working setup was just the start. We ran further evaluations to understand how the solution performed within the actual translator experience, collecting feedback and refining the feature before full rollout.

From there, we brought everything together: LLM-based instruction checks and QE-powered error detection were merged into a single, unified experience in our CAT tool.

What Translators See

Translator Copilot analyzes each segment and uses visual cues (small colored dots) to indicate issues. Clicking on a flagged segment reveals two types of feedback:

• AI Suggestions: LLM-powered compliance checks that highlight deviations from customer instructions
• Possible Errors: Flagged by QE models, including grammar issues, mistranslations, or omissions

To support translator workflows and ensure smooth adoption, we added several usability features:

• One-click acceptance of suggestions
• Ability to report false positives or incorrect suggestions
• Quick navigation between flagged segments
• End-of-task feedback collection to gather user insights

The Technical Challenges We Solved

Bringing Translator Copilot to life involved solving several tough challenges:

Low initial success rate: In early tests, the LLM correctly identified instruction compliance only 30% of the time. Through extensive prompt engineering and provider experimentation, we raised that to 78% before full rollout.

HTML formatting: Translator instructions are written in HTML for clarity. But this introduced a new issue, HTML degraded LLM performance. We resolved this by stripping HTML before sending instructions to the model, which required careful prompt design to preserve meaning and structure.

Glossary alignment: Another early challenge was that some model suggestions contradicted customer glossaries. To fix this, we refined prompts to incorporate glossary context, reducing conflicts and boosting trust in AI suggestions.

How We Measure Success

To evaluate Translator Copilot’s impact, we implemented several metrics:

• Error delta: Comparing the number of issues flagged at the start vs. the end of each task. A positive error reduction rate indicates that the translators are using Copilot to improve quality.

• AI suggestions versus Possible Errors: AI Suggestions led to a 66% error reduction rate, versus 57% for Possible Errors alone.

• User behavior: In 60% of tasks, the number of flagged issues decreased. In 15%, there was no change, likely cases where suggestions were ignored. We also track suggestion reports to improve model behavior.

An interesting insight emerged from our data: LLM performance varies by language pair. For example, error reporting is higher in German-English, Portuguese-Italian and Portuguese-German, and lower in english source language pairs such as English-Spanish or English-Norwegian, an area we’re continuing to investigate.

Looking Ahead

Translator Copilot is a big step forward in combining GenAI and linguist workflows. It brings instruction compliance, error detection, and user feedback into one cohesive experience. Most importantly, it helps translators deliver better results, faster.

We’re excited by the early results, and even more excited about what’s next! This is just the beginning.

The post Introducing Translator Copilot: Bridging Customers and Translators with AI   appeared first on Unbabel.

This quarter’s releases focus on expanding language capabilities, improving translator tools, and giving you greater control over your projects. Let’s dive into what’s new!

New TowerLLM Versions: More Languages, Better Performance

Our TowerLLM technology has leveled up with expanded coverage to 22 languages and significantly improved performance across challenging domains. We’ve enhanced customization capabilities that better adhere to brand specific tone and language requirements. Whether you’re translating technical documentation or creative marketing content, these improvements ensure consistent quality across all your multilingual communications.

PDF Translation Made Simple (BETA)

Say goodbye to document conversion headaches. You can now translate PDF documents directly in the Projects App at no additional cost. Simply upload your PDF, select the appropriate filter, and receive your translations in either PDF or Word format, streamlining your workflow and saving valuable time.

Data at Your Fingertips: Reports App Export Feature

Making data-driven decisions just got easier with our new Export Reports feature. Extract translation metrics and cost data from the Portal with a simple click, enabling seamless sharing with stakeholders and integration with your existing business intelligence systems. Whether you’re tracking performance or justifying translation investments, this feature puts the power of data in your hands.

Streamlined Project Management

Reference File Integration

Communication is key to great translations. Now you can securely upload reference files directly within the project creation flow, providing valuable context to translation teams without additional steps.

Translation Pipeline Flexibility

Why create multiple projects when one will do? Our new capability allows you to select different Translation Pipelines for each file within a single project, streamlining your workflow and saving valuable time.

Enhanced Projects App: More Control, Better Workflow

We’ve updated the Projects App with several features that give you even more control over your translation projects:

Flexible Estimation

Need to make adjustments after seeing the initial cost estimate? You can now modify your project and instantly receive updated estimates before final submission, giving you complete budget control.

Transparent Cost Tracking

Keep your finances in check with improved visibility into project costs. Once your project is complete, you’ll see the final cost directly in your project details, making expense tracking straightforward.

Versatile Content Submission

Mix and match your content submission methods by combining file uploads with pasted text in a single project. This flexibility accommodates various content types without needing to create separate projects.

Preview Before You Commit

Eliminate formatting surprises by previewing how your chosen file filter will affect your documents before submission. This visual confirmation ensures your translated content will maintain the formatting you expect.

Smarter Tools for Translators

Translator Copilot

Our new AI-powered Copilot feature is like having a quality assistant for every translator. By leveraging Quality Estimation (QE) checks and LLM suggestions, translators can quickly identify potential errors and align their work with your specific instructions. The result? Higher quality translations delivered more efficiently.

Displaying Tag Type

We’ve made the translation process more intuitive by displaying tag types directly in the editing interface. Translators can now easily identify formatting, placeholders, and custom tags, resulting in fewer errors and more confident handling of complex content.

What’s Next for Unbabel?

These releases represent our ongoing commitment to making multilingual communication more accessible, efficient, and effective for global businesses. Our product team continues to innovate based on your feedback, so stay connected for more exciting updates in the coming months.

Want to see these new features in action? Schedule a personalized demo today, or if you’re an existing customer, reach out to your Account Manager to learn how to leverage these enhancements for your specific needs.

The post Unbabel’s Latest Releases – Q1 2025 appeared first on Unbabel.

Innovative Partnership:

This partnership combines Acclaro’s industry-leading innovations in localization, cultural adaptation, and technology driven services with Unbabel’s cutting-edge AI-driven translation technology.

Together, they will deliver unparalleled translation services further empowering their shared expertise in localization for tech, media, e-commerce and fintech companies.    

Partnership Overview:

• Enhance Translation Quality with AI – Acclaro can now integrate with Unbabel’s AI-only solution Widn.Ai and leverage its AI driven quality intelligence tools and linguistic research to ensure both accuracy and cultural precision.
  
• Increased Efficiency – The integration of Acclaro’s strategic localization workflows paired with Unbabel’s advanced automation and TowerLLM will streamline translation workflows, reducing turnaround times and operational costs.
  
• Global Reach – Businesses will benefit from Acclaro’s extensive specialized linguist community and Unbabel’s scalable AI technology, to expand access to diverse markets.
  

“Combining our localization expertise with Unbabel’s innovative technology is a game-changer for the industry,” said Russell Haworth, CEO of Acclaro. “Together, we will set new standards for translation quality and operational excellence. The alignment of cutting-edge AI and the best people is the future.”

“We are thrilled to partner with Acclaro to push the boundaries of what’s possible in translation and localization,” said Vasco Pedro, CEO of Unbabel. “This collaboration will empower businesses to connect with their global audiences more effectively and efficiently.”

****ENDS****

About Unbabel

Unbabel is a leader in Translation AI, combining advanced artificial intelligence with human expertise to deliver high-quality, scalable language solutions.

Its mission is to eliminate language barriers so that businesses can thrive across cultures and geographies.

Trusted by leading global brands, Unbabel helps enterprises grow into new global markets and build customer trust by creating more consistent, high-quality multilingual customer experiences.

About Acclaro

Acclaro is a trusted localization partner to the world’s leading brands, offering strategic translation and localization services. With a focus on cultural resonance and technological innovation, Acclaro helps businesses grow their global presence and connect with customers in meaningful ways.

Media Contacts:

For more information or interview requests, please do not hesitate to reach out to our media contacts below:

• Unbabel: [email protected] 

• Acclaro: [email protected]

The post Acclaro & Unbabel Partner to Take Global AI Powered Translation Services to the Next Level appeared first on Unbabel.

Recognized as the industry gold standard for translation quality, these AI-powered tools achieve state of the art performance in translation quality evaluation. Using this technology businesses can distinguish top tier from low quality translations, cut down review time, boost efficiency, and reduce operational costs. 

Up until now most AI translation flows were “blind” when it comes to quality, and companies need to either trust that these are correct or pay for additional human in the loop support. With quality evaluation, this is no longer the case – you can continuously assess the quality of your systems – and only take action if and when required.

What was once the preserve of enterprise companies can now be leveraged by organisations of all sizes through empowering companies to scale their AI powered translation operations with confidence.

Trusted by global enterprises and major technology companies alike, COMET and QE bring different strengths to quality evaluation. COMET’s neural technology matches human judgment across 100+ languages, ensuring translations meet real-world quality standards. QE performs instant quality checks without reference texts—offering real-time insights into translation accuracy.

With Widn.AI’s API, these powerful tools are now within reach for language service providers, developers, and businesses of all sizes—without the complexity.

Vasco Pedro, Co-founder & CEO, Unbabel said: “At Unbabel, we push the limits of AI to deliver world class translation. By integrating our industry-leading COMET and QE tools with Widn.AI, we’re democratizing access to the very best quality evaluation on the market—helping businesses to scale their operations faster and more efficiently than ever before.”

Learn more about how COMET, QE can help your business scale and optimise your translations at Widn.AI

For media enquiries please contact [email protected]

ABOUT COMET and QE

COMET is a cutting-edge neural framework for translation quality evaluation, built by Unbabel to match human judgment across 100+ languages. Using advanced AI and large-scale cross-lingual models, it delivers highly accurate predictions of translation quality.

Unlike traditional metrics, COMET learns from human assessments, analyzing both source text and translations to produce quality scores that closely reflect expert evaluations. Combined with Quality Estimation (QE), which enables real-time quality checks without reference translations, COMET sets the bar for translation quality assessment.

ABOUT Widn.Ai

Widn.AI is a powerful, yet straightforward Language AI solution for businesses seeking enterprise-grade translations without enterprise-level costs. Powered by one of the world’s leading multilingual LLMs, Widn.AI delivers natural, authentic translations that capture true meaning, not just words.

Developed by Unbabel’s world-class research team, Widn.AI is built to scale with your business needs, helping organizations scale confidently across languages and markets.

Our goal is simple: help businesses grow faster with world class Language AI.

The post Unbabel Supercharges Widn.Ai with Quality Evaluation appeared first on Unbabel.

• Founded: 2014, Hamburg, Germany
• Serves over 12 million customers  
• Offers support in 26 European markets and 25 languages

The challenge

AboutYou, a leading digital fashion and lifestyle retailer, offers a wide range of apparel, accessories, and footwear to customers across multiple markets. Renowned for its innovative approach to personalization, About You creates a highly tailored shopping experience, setting a benchmark for e-commerce excellence. However, offering personalized, on-time and on-brand support across European markets, while delivering on growth targets, is no small task.

Managing volume spikes is a critical challenge for any retailer, and also a key opportunity to grow revenue. Whether spikes come from marketing campaigns, supplier challenges, or the behemoth of Black Friday, AboutYou needed a way to scale customer service resources without constantly hiring or incurring large costs, while maintaining a consistent, quality support experience.

“We consistently faced the costly challenge of ramping up and down short-term resources for our campaigns. This is where Unbabel came into play, helping us to flexibly allocate our existing resources across markets that are the focus of these campaigns. Unbabel provided quick, straightforward processes from implementation to agent training and tool utilization, making it an efficient solution for our needs.”

– René Fischer, Senior Customer Service Controller & Product Admin

The solution

AboutYou selected Unbabel’s AI-powered translation platform, combining machine and human translation to meet a variety of quality needs, to address this customer service growth challenge. Unbabel was chosen for its ability to provide:

• Quality: Unbabel’s high-quality translations ensures AboutYou maintains its commitment to providing excellent support – even during peak periods. 
• Simplicity: Unbabel’s onboarding process and integration into existing systems like Zendesk are seamless, simplifying the implementation and agent training process for AboutYou.
• Partner Approach: Unbabel’s mix of dedicated support, deep linguistic expertise and developing tailored solutions to meet AboutYou’s specific needs showed the level of investment into the relationship.

The results

By integrating Unbabel into Zendesk and progressively rolling out the solution across languages, AboutYou achieved significant improvements in its customer service operations:

• Cost Savings: Black Friday in particular is a challenge in retail and ecommerce, and AboutYou was able to accrue savings in the six-figure range during Black Friday by avoiding the need to hire and train additional customer service representatives.
• Consistent Performance: There was no negative impact with Unbabel on KPIs like Service Level Agreements (SLAs), Customer Satisfaction (CSAT) scores, handling times, or the overall customer experience. 
• Strengthened Partner Relations: AboutYou received positive feedback from its outsourcing partners. The new flexibility let these partners reduce frequent staffing adjustments, improving stability and employee retention.

“Despite initial doubts, the tool has proven to be extremely user-friendly. The biggest advantage is that ticket handling is hardly any different from the way I’m used to handling tickets in my native language. The handling is intuitive and smooth, so that the workflow remains uninterrupted, and the tool is quick and easy to use. Unbabel makes a significant contribution to overcoming language barriers without complicating the work process.”

– AboutYou Customer Support Agent

Managing Spikes in Action: Black Friday

Black Friday clearly demonstrates the flexibility AboutYou enjoys with Unbabel. With massive customer service spikes, AboutYou was able to much more smoothly manage the volume without increasing headcount. 

With Unbabel, AboutYou strategically deploys resources to address the early peaks in Romania and Bulgaria, where Black Friday starts earlier. By deploying Unbabel-supported agents to these spikes, AboutYou didn’t have to recruit and train on short notice. As volume in Romania and Bulgaria subsided, but surged in Germany, Austria and Switzerland, AboutYou re-allocated these resources seamlessly, again without the churn of hiring and training. 

This flexibility allows AboutYou to successfully manage the Black Friday surge without having to hire additional staff. By shuffling the team based on capacity, rather than language skill, they could avoid an increase in FTEs in the mid double digits, and the associated cost of mid five-figures per FTE. This corresponding savings lets AboutYou invests where it matters – in the customer experience.

Unbabel’s AI-powered translation platform lets AboutYou efficiently manage customer service operations, particularly during periods of high demand. By making their agents multilingual, AboutYou can flexibly use resources to meet spikes wherever they are, and support the businesses revenue and marketing goals, no matter the market, while still meeting the high standards of support and customer experience AboutYou has set. 

Looking to expand across markets or optimize your multilingual operations with on-brand quality? Unbabel can help.

The post How AboutYou scales customer support around big retail spikes appeared first on Unbabel.

Built from scratch on extensive training data on MareNostrum 5 at the Barcelona Supercomputing Center leveraging the advanced European HPC infrastructure for large-scale training. The model outperforms most global models of similar size and signals a win for Europe’s mission to accelerate the pace of homegrown AI innovation.

Europe is the only continent in the world to have a large public network of supercomputers, managed by the EuroHPC Joint Undertaking (EuroHPC JU). It has succeeded in holding its own in the global race for GPU access and in the latest Top500 ranking of the world’s fastest machines, two out of the Top 10 and within the top 200, with this number increasing soon with the upcoming launch of two new exascale computers.

As a highly advanced “EU-made” multilingual AI model, the release marks a significant step in Europe’s drive to lead in multilingual AI innovation. It aims to set a new standard for multilingual LLMs with best in class task specific accuracy, efficiency, and speed.  

EuroLLM is completely open so anyone from individuals to startups, researchers and beyond can build on top of it.This openness aims to serve as a flywheel for EU homegrown innovation by reducing barriers to entry for smaller enterprises, encouraging experimentation, and help accelerate AI-led innovation in Europe.

While its initial focus is multilinguality—supporting all 24 official EU languages as well as 11 additional languages—the EuroLLM project has an ambitious roadmap with new, larger models on the make and plans to expand its capabilities to encompass speech and vision capabilities.

EuroLLM was developed by a consortium of partners including Unbabel, Técnico, Instituto de Telecomunicações, University of Edinburgh, Paris-Saclay University, Aveni, Paris Sorbonne University, Naver Labs, and University of Amsterdam, supported by Horizon Europe, the EU’s flagship research and development initiative. The initiative is supported by a EuroHPC Extreme Scale Access call. 

One of the major challenges in the development of large language models (LLMs) is the persistent English language bias. EuroLLM emerged from a pressing need to bridge gaps in language access across the EU and create a model tailored to the linguistic and cultural diversity of Europe.

Andre Martins, Unbabel’s VP of AI of Research and Professor at Técnico, says: ‘We’re very proud to launch EuroLLM today. This model has come to life through our team working relentlessly to develop it at breakneck speed and ensuring the greatest quality through careful data filtering. 

We see this as an exciting first step to closing the global innovation gap and strengthening Europe’s digital sovereignty, which is more important now than ever before. Our goal is that EuroLLM becomes a flywheel for innovation with the opportunity for anyone to use this EU homegrown LLM and develop on top of it. EuroLLM is also a success story for the European supercomputing network and how it can help advance AI—proof that amazing things can happen through open collaboration across multiple organizations. This model is fully open, so we actively encourage everyone to use it, improve it, and develop new technology on top of it.”

With major players like OpenAI, Google, and Meta dominating the AI landscape, reliance on their models poses significant risks, including limited openness and uncertain future availability. EuroLLM  aims to counter this trend by offering an open and accessible alternative designed to serve Europe’s needs without compromising its independence.

By prioritizing transparency and accessibility, the EuroLLM Consortium has created a model that aligns with the EU’s core values, while ensuring that Europe retains control over its critical AI infrastructure. The ability to support all official EU languages and the potential of this model to drive inclusive innovation across the continent, from public services to private enterprise was at the heart of its premise.

EuroLLM is available via Hugging Face today—here you can see more technical information and comparison with other models in public benchmarks.

For more information or interview requests please contact [email protected]

About the EuroLLM Consortium
The EuroLLM Consortium brings together Unbabel, Técnico, Instituto de Telecomunicações, the University of Edinburgh, Paris-Saclay University, Aveni, Sorbonne University, Naver Labs, University of Amsterdam among Europe’s leading AI researchers to create cutting-edge, ethical, and multilingual AI technologies. With a mission to strengthen Europe’s digital sovereignty, the consortium develops solutions that reflect the EU’s commitment to innovation, diversity, and independence.

About Unbabel’s Research Science Team
Comprised of experts committed to advancing the frontiers of language technologies, the Unbabel Research team specializes in long-term multilingual NLP challenges, particularly in advancing Machine Translation (MT) and Quality Estimation (QE) technologies. Their groundbreaking work aims to revolutionize language translation systems and enhance global communication and understanding. Currently, the team is focused on developing and refining multilingual large language models, taking us closer to Unbabel’s vision: creating a world without language barriers. Unbabel’s research team were the brains behind the creation of Unbabel’s latest product – Widn AI. Widn is a smart, straightforward Language AI solution built for businesses who want reliable, fast and high-quality translations without the high cost.

The post Europe steps up its game to boost AI sovereignty with launch of ‘EuroLLM’ appeared first on Unbabel.

Widn is powered by the world’s leading multilingual LLM. Its language model recently outperformed GPT, DeepL, and Google Translate coming out on top across 8 out of 11 language pairs as recognised by the WMT, the benchmark authority in translation quality for the industry.

Widn’s platform is set to be a game-changer, designed to help businesses save time, cut costs and ultimately boost efficiency and bottom lines. With two-thirds of the global population now online, demand for digital content and e-commerce in native languages has never been higher.

One key aspect of effective translation is not just the ability to translate word-for-word, but also to capture subtleties and nuances. Widn exemplifies this by not just translating but truly understanding and capturing meaning. Its advanced AI goes beyond literal translation, grasping the intricacies of context. It also enhances and polishes content, delivering not only accuracy but unlocking meaningful communication across multiple languages. 

Vasco Pedro, founder and CEO of Unbabel said: “We’re excited to launch Widn.AI today. This milestone comes after 18 months of focused development, during which we’ve worked tirelessly to create a state-of-the-art LLM that sets a new standard for translation. Large language models are the closest we have to true intelligence and with Widn’s LLM, we believe we’ve achieved the highest level of translation performance. Now we’re ready to open up this innovation to wider audiences and take the technology to the next level”.

Its Generative AI language model, recognized for delivering exceptional quality across both general and specialized domains, including medical and legal, leverages over a decade of high-quality, proprietary data curated by translation experts. Coupled with Unbabel’s industry-leading quality model, COMETKiwi (Qi), it ensures unparalleled accuracy and authenticity in every translation.

The longer-term ambition for Widn is to evolve and plans to scale into future modalities, including audio and video to become the world’s go to ‘communication LLM’ It marks a new chapter for multilingual LLMs, as the market is ready to embrace these models as standalone solutions.

Vasco continued:  “With Widn.AI, it is our top priority to democratize access to high-quality Language AI in line with growing demand. Unlike with Unbabel, we aren’t actively targeting larger enterprises with extensive localization teams and operations. This is about empowering businesses of all sizes to grow and scale globally.”

The rapid rise of ‘prosumers’—individuals who actively engage in creating and consuming content—continues to reshape the digital landscape. With increasing influence, prosumers have evolved from passive consumers to active creators for brands and have significantly enriched the content ecosystem.

Widn aims to target this growing, new wave of customers by delivering an AI platform that is tailored to users that want to communicate in a more vibrant way by placing resonance at the heart of its proposition. In doing so, it seeks to help users to not only increase their authenticity with target audiences but also gain a competitive edge.

In the coming months, Widn is set to focus on meeting the evolving demands of the digital content landscape and diverse content types. It is committed to driving innovation and continuous improvement, serving as a trusted solution designed to empower ambitious businesses looking to navigate the complexities of global communication in a straightforward way.

About Widn.Ai

Widn.AI is a smart, straightforward Language AI solution built for businesses who want reliable, high-quality translations without the high cost. Powered by the world’s best multilingual LLM, Widn.AI goes beyond simple word-for-word translation, capturing meaning to make your message sound authentic. It’s more than just a translation tool—it helps you communicate clearly and effectively in any language.

Widn.AI is designed to grow and adapt to future language needs – our goal is simple: help businesses grow faster with world class Language AI.

Widn.AI was developed by Unbabel’s world class research science team.

For media enquiries or interview requests please contact [email protected]

The post Unbabel backs LLMs to lead the future of Language AI with launch of Widn.AI appeared first on Unbabel.

This research brief independently conducted by CSA Research sheds light on the impact of LLMs and what they mean for the future of translation, as well as covering what our own TowerLLM is capable of.

Download the research brief now to learn:

• What advantages LLMs offer over NMT
• What makes our own TowerLLM special compared to other LLMs
• How LLMs can help consolidate AI vendors and tighten data security
• What benefits LLMs can deliver in personalized customer interactions

The post An Analysis of LLMs in Translation appeared first on Unbabel.