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Now available—a next generation enterprise studio for AI builders to train, validate, tune and deploy AI models

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Our next-generation enterprise studio for AI builders

IBM® watsonx.ai™ AI studio is part of the IBM watsonx™ AI and data platform, bringing together new generative AI (gen AI) capabilities powered by foundation models and traditional machine learning (ML) into a powerful studio spanning the AI lifecycle. Tune and guide models with your enterprise data to meet your needs with easy-to-use tools for building and refining performant prompts. With watsonx.ai, you can build AI applications in a fraction of the time and with a fraction of the data. Watsonx.ai offers:

  • Multi-model variety and flexibility: Choose from IBM-developed Granite models, open-source and third-party models, or bring your own model.
  • Differentiated client protection: IBM stands behind IBM-developed Granite models and indemnifies the client against third-party IP claims.
  • End-to-end AI governance: Enterprises can scale and accelerate the impact of AI with trusted data across the business, using data wherever it resides.
  • Hybrid, multi-cloud deployments: IBM provides the flexibility to integrate and deploy your AI workloads into your hybrid-cloud stack of choice.
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Use cases

Bring your own custom foundation models or work with a suite of curated foundation models offered by IBM, including Granite models. Experiment with open source models through the IBM and Hugging Face partnership to meet the needs of your business.

Collect, create and share knowledge Build a Q&A resource from a broad internal or external knowledge base across your company’s proprietary data to share organizational insights. With the help of generative AI, you can analyze multiple documents and data inputs, provide effective responses based on real-time information feeds and improve documentation quality. Learn more

Extract insights and discover trends Analyze large amounts of data to identify and extract insights or facts from documents or reports, customer interactions, security or IT incidents. Discover patterns, trends or anomalies that occur within the data with the use of generative AI. From the themes extracted, traditional AI and ML algorithms can then forecast and make predictions, such as calculating credit risk, future sales, demand forecasts and inventory management, specific to the user's needs and business requirements. 
Generate synthetic tabular data Generate synthetic tabular data to protect sensitive information during testing stages. Address data gaps and reduce the risk of exposing an individual’s personal data by taking advantage of data created artificially through computer simulation or algorithms. Further build and test AI and ML models with synthetic data to overcome data gaps and, in turn, improve speed to market with new AI solutions.

Generate content, technology and code New technology, content and code can be created through the power of generative AI to support developer and business user productivity across a range of business domains. The content generated can include lesson planning and curriculum development, ideas for marketing and sales campaigns, emails, blogs, social media posts, product demonstrations, synthetic data images, technical documentation, user persona development, automated reports, scripts and more.

Benefits Discover how to scale AI Bring together AI builders

Use open-source frameworks and tools for code-based, automated and visual data science capabilities–all in a secure, trusted studio environment.

Tune foundation models for your business

Leverage foundation models and generative AI with minimal data, advanced prompt-tuning capabilities, full SDK and API libraries.

Manage the full AI lifecycle

Accelerate the full AI model lifecycle with all the tools and runtimes in one place to train, validate, tune and deploy AI models across clouds and on-premises environments.

Foundation models Clients can bring in IBM-supported custom foundation models from Hugging Face and have access to other third-party models including Llama 3 and Mixtral 8x7b. They also have access to a family of IBM-developed foundation models of different sizes and architectures, including open-source Granite models and IBM customized Granite models to support enterprise domains and use cases such as RAG. See foundation models in watsonx.ai Explore how to choose the right foundation model

Prompt Lab Where AI builders can work with foundation models and build prompts using prompt engineering. Within the Prompt Lab, users can interact with foundation models in the prompt editor using the Chat, Freeform or Structured mode. These multiple options will allow you to craft the best model configurations to support a range of Natural Language Processing (NLP) type tasks including question answering, content generation and summarization, text classification and extraction.

Tuning Studio Prompt-tune foundation models as part of our Tuning Studio to help tune your foundation models with labeled data for better performance and accuracy. Prompt-tuning is an efficient, low-cost way of adapting a foundation model to new downstream tasks without retraining the model and updating its weights. Once your model is tuned, you can start using it in the Prompt Lab. Subsequent releases will include capabilities for model fine-tuning as part of our Tuning Studio.

Public preview now available Flows engine With its intuitive flow language, watsonx.ai flows engine simplifies the development process, allowing generative AI applications to be effortlessly deployed to the cloud, accessed via API calls or SDKs, and integrated into existing projects and architectures. The feature provides a range of pre-built AI flows for tasks such as Retrieval Augmented Generation (RAG) and Summarization, allowing developers to embed AI into their business processes seamlessly. Learn more about flows engine

Data science and MLOps All the tools, pipelines and runtimes powered by foundation models, a data scientist would need to support building ML models automatically. Automate the entire AI model lifecycle from development to deployment with connections to a variety of APIs, SDKs and libraries.

Gen AI capabilities

In the Prompt Lab, leverage foundation models to create better AI, faster. Experiment with different prompts for various use cases and tasks. With just a few lines of instruction you can draft job descriptions, classify customer complaints, summarize complex regulatory documents, extract key business information and much more. Quickly tune models for your specific business needs using the latest open source and IBM trained foundation models.

Generate content, no code required From writing marketing emails to creating customer personas, watsonx.ai is your new creative partner. Just specify what you want, set the parameters and let the AI do the work.

Build a classifier without training With as few as zero examples, watsonx.ai can read and classify written input. For example, it can evaluate and sort customer complaints or review customer feedback sentiment.

Save time with high-quality summaries Like a skilled assistant, watsonx.ai can help transform dense text into your personalized executive overview, capturing key points from financial reports, meeting transcriptions and more.

Extract information with no pre-training Let watsonx.ai sort through the complex details and help you quickly pull the information you want from large documents. Identify named entities, parse terms and conditions and more.

Enhance your Q&A application Leverage retrieval-augmented generation (RAG) to generate factually accurate output that is grounded in a broad external or internal knowledge base.

MLOps capabilities

Build models either visually or with code, deploy and monitor with end-to-end lifecycle explainability and fairness. Use MLOps to simplify model production from any tool and provide automatic model retraining.

Create automated pipelines Single collaborative studio for data scientists to build, train and deploy ML models. It supports a wide range of data sources enabling teams to streamline their workflows. With advanced features like automated ML and model monitoring, users can manage their models throughout the development and deployment lifecycle.

Solve optimization problems Uncover prescriptive analytics to improve your business decisions, such as planning, scheduling, pricing, inventory or resource management with CPLEX Optimizer. These CPLEX decision optimization engines apply specialized mathematical algorithms and constraint-based programming to address your business objectives. Within the CPLEX solver, access tabular or graphical views that can be easily shared to enhance collaboration and accelerate time to insights.
Develop predictive models visually With easy-to-use workflows, you can combine visual data science with open source libraries and notebook-based interfaces on a unified data and AI studio.

Accelerate the entire AI lifecycle With AutoAI, beginners can quickly get started and expert data scientists can speed experimentation in AI development. AutoAI automates data preparation, model development, feature engineering and hyperparameter optimization.

Generate synthetic tabular data Generate a synthetic tabular data set leveraging your existing data or a custom data schema. You can connect to your existing database, upload a data file, anonymize columns and generate as much data as needed to address your data gaps or train your classical AI models.

Partner with us to deliver enhanced commercial solutions, embedded with watsonx.ai, to better address clients’ needs.
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1IBM’s statements regarding its plans, directions, and intent are subject to change or withdrawal without notice at IBM’s sole discretion. See Pricing for more detail. Unless otherwise specified under Software pricing, all features, capabilities, and potential updates refer exclusively to SaaS. IBM makes no representation that SaaS and software features and capabilities will be the same.