Intento, Inc.

Intento, Inc.

Software Development

Berkeley, CA 6,085 followers

Machine Translation and AI Agents for enterprise localization.

About us

Intento builds AI agents for enterprise localization using machine translation and multilingual generative AI. Its Enterprise Language Hub enables companies like Procore and Subway to deliver consistent, authentic language experiences across all markets and audiences. It combines machine translation and generative AI models into multi-agent AI workflows, customizing them to client data and integrating them into customers’ existing software systems for localization, marketing, customer support, and other business functions. With Intento, clients achieve high-quality, real-time translations for all users and team members worldwide. The Enterprise Language Hub is ISO-27001 certified, ensuring enterprise top-tier security for GenAI solutions in high-demand industries. Intento also offers ISO-9001-certified expert help for setting up and maintaining MT and AI models and constantly refines these models with new data and user feedback.

Website
http://inten.to
Industry
Software Development
Company size
51-200 employees
Headquarters
Berkeley, CA
Type
Privately Held
Founded
2016
Specialties
Artificial intelligence, Enterprise Software, Machine Translation, and Localization

Locations

Employees at Intento, Inc.

Updates

  • View organization page for Intento, Inc., graphic

    6,085 followers

    🎉 We’ve published our 8th annual State of Machine Translation report. It analyzes 52 MT engines and LLMs across 11 language pairs and 9 content domains. Get your copy here ➡️ https://hubs.la/Q02zD6Z70 Here’re some key findings: 🎯 LLMs reshaped the MT landscape and now account for 55% of top-performing models 🎯 Quality varies by language and domain, with LLMs excelling in Colloquial, Education, and Entertainment 🎯 Traditional Machine Translation (MT) still outperforms in specific language pairs and domains 🎯 LLMs are less expensive but slower than MT engines 🎯 Open-source LLMs lag behind commercial offerings 🎯 Customization through translation memories, glossaries, and prompt engineering is key to eliminating errors Explore the full report to learn more about the evolving capabilities and potential of LLMs. e2f, inc.

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  • View organization page for Intento, Inc., graphic

    6,085 followers

    Tired of so much budget going toward post-editing? Check out this video and learn how AI Agents can help. If you’re attending #LocWorld52, stop by our booth №109 to discuss how this technology can boost your success in 2025!

    View profile for Konstantin Savenkov, graphic

    CEO @ Intento - AI agents for enterprise localization.

    Even with the best MT systems, companies still spend 95-98% of their localization budgets on human post-editing. Why? Because while MT excels at learning common patterns, many localization requirements are too nuanced or context-dependent to be learned from data alone. The solution? AI agents that can be instructed, not just trained. At Intento, we've developed a multi-agent platform that bridges the gap between raw MT output and enterprise requirements. Our early-access customers are already seeing how these specialized AI agents can handle things like tone adjustment, gender forms, and style guide compliance. This isn't about replacing translators – it's about elevating their work. By automating repetitive fixes, we're freeing up talented professionals to focus on what they do best: bringing cultural nuance and creativity to translations. Want to learn more? Visit us at our Locworld booth to see how this technology could transform your 2025 localization strategy. #LLM #AI #agents #Localization #MachineTranslation #Locworld52

  • View organization page for Intento, Inc., graphic

    6,085 followers

    💥 Join our webinar with XTM International to explore how Large Language Models (LLMs) compare to Traditional Machine Translation (MT) systems in terms of quality, adaptability, and cost ➡️ https://hubs.la/Q02VRDlM0 👀 We’ll share what we’ve recently discovered about: • Quality, analyzing where LLMs outperform traditional MT and how both handle errors • Adaptability, comparing how well LLMs and traditional MT handle specialized translations • Cost differences and when LLMs become more cost-effective • We’ll also compare the speed of LLMs and traditional MT for large-scale tasks, discussing current limitations and factors affecting performance. 🚀 Don’t miss this opportunity to hear from industry experts and ask all your questions during the live Q&A session!

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  • View organization page for Intento, Inc., graphic

    6,085 followers

    Join us today at TAUS for a panel discussion on Questioning Quality and Evaluating LLMs. The panel will focus on building trust in automated language solutions and effective evaluation strategies for multilingual content. We’ll discuss the state of the art in automatic translation quality evaluation and what’s changing as LLMs rapidly take over the language industry. Speakers: Konstantin Savenkov (Intento), Amir Kamran (TAUS), Adam Bittlingmayer (Modelfront), Alex Yanishevsky (Smartling), Ilan Kernerman (Lexicala). Moderated by Dace Dzeguze (TAUS). #TAUS #TAUSmassivelymultilingual

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  • View organization page for Intento, Inc., graphic

    6,085 followers

    Are you at AMTA today? 👀 Konstantin Savenkov, Intento’s CEO and co-founder, will present the State of Machine Translation 2024 in person. In this study, we evaluated 52 machine translation systems, including 24 LLMs, across 11 language pairs and 9 domains. Get the full report here ➡️ https://hubs.la/Q02RxyVd0. You’ll learn how LLMs are taking over the machine translation market, their strengths and weaknesses, and where older technologies still outperform the new ones. Join us to get your questions answered directly! 💥 #AMTA

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  • View organization page for Intento, Inc., graphic

    6,085 followers

    We’re expanding our study on using AI to evaluate Machine Translation 🚀 This time, we’ve tested models from OpenAI, Google, Anthropic, and open-source options across three language pairs and eight domains. Our goal is to find how well various Large Language Models perform translation quality checks. We’re measuring how well they match human judgments on error types, severity, and overall quality scores. The results will help create a more efficient quality assessment process. 👉 Join us at AMTA today to learn more from Daria Sinitsyna, our Lead Computational Linguist. You’ll find out which AI models best evaluate machine translation quality across multiple languages and new tips for building a more efficient quality check system. #AMTA

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  • View organization page for Intento, Inc., graphic

    6,085 followers

    We’ve increased our range of Atlassian solutions and made it easier for everyone to communicate and share knowledge in Confluence Data Center with our new Translator for Confluence. Your team needs to access content every day and when they speak multiple languages it is hard to keep up with the demand for translation. Now, with the Intento Translator for Confluence, when someone writes, searches, and reads Confluence pages or leaves comments, everything automatically translates in real-time, while keeping your terminology, style, and tone of voice. This means that everyone can access and search for content in the language they are most comfortable with, making it easier to work together. Book a demo today to learn more ➡️ https://hubs.la/Q02Rksq_0

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