What Integrates with IBM Watson Language Translator?

Find out what IBM Watson Language Translator integrations exist in 2025. Learn what software and services currently integrate with IBM Watson Language Translator, and sort them by reviews, cost, features, and more. Below is a list of products that IBM Watson Language Translator currently integrates with:

  • 1
    Crowdin Reviews
    Top Pick

    Crowdin

    Crowdin

    $50.00/month
    724 Ratings
    See Software
    Learn More
    Get quality translations for your app, website, game, supporting documentation, and on. Invite your own translation team or work with professional translation agencies within Crowdin. Features that ensure quality translations and speed up the process • Glossary – create a list of terms to get consistent translations • Translation Memory (TM) – no need to translate identical strings • Screenshots – tag source strings to get context-relevant translations • Integrations – set up integration with GitHub, Google Play, API, CLI, Android Studio, and on • QA checks – make sure that all the translations have the same meaning and functions as the source strings • In-Context – proofreading within the actual web application • Machine Translations (MT) – pre-translate via translation engine • Reports – get insights, plan and manage the project Crowdin supports more than 30 file formats for mobile, software, documents, subtitles, graphics and assets: .xml, .strings, .json, .html, .xliff, .csv, .php, .resx, .yaml, .xml, .strings and on.
  • 2
    PubNub Reviews
    One Platform for Realtime Communication: A platform to build and operate real-time interactivity for web, mobile, AI/ML, IoT, and Edge computing applications Faster & Easier Deployments: SDK support for 50+ mobile, web, server, and IoT environments (PubNub & community supported) and more than 65 pre-built integrations with external and third-party APIs to give you the features you need regardless of programming language or tech stack. Scalability: The industry’s most scalable platform capable of supporting millions of concurrent users for rapid growth with low latency, high uptime, and without financial penalties.
  • 3
    IBM Data Refinery Reviews
    The data refinery tool, which can be accessed through IBM Watson® Studio and Watson™ Knowledge Catalog, significantly reduces the time spent on data preparation by swiftly converting extensive volumes of raw data into high-quality, usable information suitable for analytics. Users can interactively discover, clean, and transform their data using more than 100 pre-built operations without needing any coding expertise. Gain insights into the quality and distribution of your data with a variety of integrated charts, graphs, and statistical tools. The tool automatically identifies data types and business classifications, ensuring accuracy and relevance. It also allows easy access to and exploration of data from diverse sources, whether on-premises or cloud-based. Data governance policies set by professionals are automatically enforced within the tool, providing an added layer of compliance. Users can schedule data flow executions for consistent results and easily monitor those results while receiving timely notifications. Furthermore, the solution enables seamless scaling through Apache Spark, allowing transformation recipes to be applied to complete datasets without the burden of managing Apache Spark clusters. This feature enhances efficiency and effectiveness in data processing, making it a valuable asset for organizations looking to optimize their data analytics capabilities.
  • 4
    IBM Watson Studio Reviews
    Create, execute, and oversee AI models while enhancing decision-making at scale across any cloud infrastructure. IBM Watson Studio enables you to implement AI seamlessly anywhere as part of the IBM Cloud Pak® for Data, which is the comprehensive data and AI platform from IBM. Collaborate across teams, streamline the management of the AI lifecycle, and hasten the realization of value with a versatile multicloud framework. You can automate the AI lifecycles using ModelOps pipelines and expedite data science development through AutoAI. Whether preparing or constructing models, you have the option to do so visually or programmatically. Deploying and operating models is made simple with one-click integration. Additionally, promote responsible AI governance by ensuring your models are fair and explainable to strengthen business strategies. Leverage open-source frameworks such as PyTorch, TensorFlow, and scikit-learn to enhance your projects. Consolidate development tools, including leading IDEs, Jupyter notebooks, JupyterLab, and command-line interfaces, along with programming languages like Python, R, and Scala. Through the automation of AI lifecycle management, IBM Watson Studio empowers you to build and scale AI solutions with an emphasis on trust and transparency, ultimately leading to improved organizational performance and innovation.
  • Previous
  • You're on page 1
  • Next