Couchbase Unveils Capella AI Services to Streamline Enterprise AI Development and Deployment

Couchbase introduces Capella AI services for AI agent design and deployment - SiliconANGLE

Couchbase introduces Capella AI services for AI agent design and deployment Database company Couchbase Inc. is looking to support the development of artificial intelligence-powered agents with the addition of Capella AI Services to its flagship cloud data platform, Couchbase Capella. Announced today, the Capella AI Services are supposed to help companies address some of the most pressing challenges they face during AI development and deployment. AI agents are one of the hottest trends in AI at the moment, referring to intelligent applications that can automate actions and tasks on behalf of users with minimal supervision. Think an AI customer support chatbot that can automatically process a refund request, or a virtual assistant that can book a hotel on someone's behalf and add that booking to their calendar. The new services, available in preview today, include model hosting, automated vectorization, unstructured data preprocessing and AI agent catalog capabilities. Essentially, the company is bundling everything developers require to prototype, build, test and then deploy their AI agents, while ensuring both the underlying data and the models are stored close together. Couchbase Capella is the cloud-based version of the open-source Couchbase NoSQL database, and its main advantage compared to traditional databases like Oracle is that it can process both structured and unstructured information, which makes it an ideal choice for applications that need to access both types of data. It also acts as a data cache. Over the last year, Couchbase has enhanced Capella's capabilities in an effort to position it as the database of choice for AI developers. In February, it introduced vector search and retrieval-augmented generation capabilities, while integrating AI frameworks such as LlamaIndex and LangChain to support the development of generative AI applications. Then in September, the company further enhanced Capella's AI capabilities with Capella Columnar, to support the development of more advanced generative AI applications that can analyze real-time data to deliver more personalized experiences. According to Couchbase, the new Capella AI Services are meant to address concerns enterprises have around performance, latency, control, costs, data security and privacy, as well as the need to manage different kinds of datasets and integrations. They include model services consisting of managed endpoints for dozens of leading large language models and embeddings models, together with value-added capabilities such as prompt and conversation caching, AI guardrails and keyword filtering. According to Couchbase, these features are necessary to support both RAG and agentic AI. Capella's AI Services also extend to unstructured data, enabling developers to extract, clean and transform unstructured documents into a more flexible JavaScript Object Notation or JSON data format, so they can be stored as vectors and accessed and queried by AI models more easily. The vectorization process can be automated too, enabling unstructured information to be indexed in Capella to support the creation of RAG pipelines. Then there are new AI agent catalog services that aim to accelerate the development of AI agents, providing a centralized repository for tools, prompts and metadata to support LLM flows, traceability and governance, the company said. These services can also automate the discovery of other agent-based tools needed to answer user's questions and manage AI guardrails. Matt McDonough, Couchbase's senior vice president of product and partners, said AI agents need to be able to handle a diverse range of data formats to work effectively. "Couchbase is making this possible by providing a comprehensive AI-powered developer data platform that streamlines RAG pipelines, ensures fast and secure model interactions and enables agent reuse during development and production," he said. "We're helping customers through the broad spectrum of AI advances, from simple vector search to RAG chatbots and sophisticated agentic AI apps." Elsewhere, the new Capella AI functions are intended to support AI-driven data analytics, classification and summarization within application workflows using the familiar SQL++ programming language syntax. This means developers don't need to worry about external tooling or custom coding, Couchbase says. McDonough explained that today's enhancements provide developers with a unified platform complete with specialized data management tools to handle the complex workflows and LLM interactions needed to power AI agents. By unifying all of these tools, the company is helping developers to avoid problems around excess latency and high operational costs, while mitigating privacy and safety issues, he added. Carl Olofson, an analyst at International Data Corp., said another challenge for organizations is that they're required to preserve and analyze all of the interactions between humans and AI agents to ensure ongoing accuracy, reliability and safety for users. He said that's what Couchbase is addressing with today's updates. "Couchbase Capella and its new AI Services are designed to strategically address these challenges, and provide enterprises the scalable architecture and flexibility needed to handle complex RAG workflows and manage huge volumes of new types of AI data," the analyst said.

Couchbase Accelerates AI Agentic Application Development With New Database Services

The addition of AI services to the company's Capella cloud database and development platform will provide developers with more control over data, development workflows and AI models. Couchbase is adding new artificial intelligence capabilities to its Capella cloud database that the company says will streamline the development of agentic AI applications. The new Capella AI Services, unveiled Monday, provide developers with simplified data integration workflows and more control over data throughout the development lifecycle including putting agentic applications into production, according to Couchbase. The AI services also help developers mitigate data security and privacy risks by keeping data and large language models - including LLMs running outside of an organization - close together. [Related: Meeting The Exploding Demand For Data: The 2024 CRN Big Data 100] With the new Capella AI Services, Couchbase, based in Santa Clara, Calif., is looking to provide data management capabilities needed for the growing wave of AI and generative AI applications development. "This release is all about our offering, really targeted at developers building AI and agentic or multi agentic applications," said Matt McDonough, Couchbase senior vice president of product and partners, in an interview with CRN. "There's a lot of enthusiasm around AI agents, but the industry as a whole lacks well-defined best practices for building and deploying these agentic applications." The new AI services come on the heels of Couchbase's September announcement of expanded columnar and vector search functionality in the Capella database-as-a-service for developing next-generation adaptive applications - including those with AI functionalities. Capella is based on Couchbase's NoSQL database server. "The key is [to] make it simple for developers to build, test and deploy AI agents without having to use disparate platforms," McDonough said. "And do this in a way that reduces latency, operational costs [and] keeping models and data close together as part of this whole agentic AI software development life cycle." The new AI services are also an enabler for Retrieval-Augmented Generation workflows that move proprietary data into LLMs, according to the executive. The new AI services include model hosting, automated vectorization, unstructured data preprocessing and AI agent catalog services - all of which allow developers to prototype, build, test and deploy AI agents. In addition to keeping models and data close together, the services help organizations reduce development complexity, avoid excess latencies and high operational costs often experienced when introducing new technology components and workflows, according to Couchbase. "The greatest strength of AI is its ability to process unstructured data," McDonough said. AI agents can take unstructured information, such as a transcription of a meeting, and autonomously incorporate it into operational applications and workflows. But AI agents need flexible databases with the ability to work with complex data types and unstructured data - such as PDF documents and audio files - to be effective, he said. Couchbase ISV and systems integrator partners will particularly benefit from the new AI Services, McDonough said. ISV partners who develop their applications on the Capella platform can better meet customer requests to add AI agent capabilities to those applications. And global and regional systems integrators can use the new functionality to expand the range of development services they can provide their customers, he said. The new Capella AI Services include: The AI services are currently in private preview and are slated to be generally available as part of the Capella cloud database in 2025.

Enterprise AI gets closer to data with Couchbase's new Capella AI services

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Database platform developer Couchbase is looking to help solve an increasingly common problem for enterprise AI deployments. Namely how to get data closer to AI in as fast and as secure an approach as possible. The end goal is to make it simpler and more operationally efficient to build and deploy enterprise AI. Couchbase today announced Capella AI Services, a suite of capabilities designed to help enterprises build and deploy AI applications while maintaining data security and streamlining development workflows. Among the new offerings is the model service for secure hosting of AI models within organizational boundaries. The vectorization service automates vector operations for efficient AI processing. AI functions simplify AI integration through SQL++ queries while the new agent catalog centralizes AI development resources and templates. The announcement comes as organizations grapple with integrating AI into their existing applications while managing concerns about data privacy, operational complexity and development efficiency. According to the company, the Capella AI Services will enable enterprises to build and deploy AI applications more efficiently with lower latency leading to improved business outcomes. This expansion builds upon Couchbase's existing strengths in NoSQL database technology and its cloud-to-edge capabilities. Couchbase is among the early pioneers in the NoSQL database world with the company going public back in 2021. Over the past year, the company has increasingly focussed on building out vector database capabilities. Those capabilities have included an assistive gen AI feature known as Cappella IQ in 2023 and expanded vector search this year. "We're focusing on building a developer data platform for critical applications in our AI world today," Matt McDonough, SVP of product and partners at Couchbase, told VentureBeat. "Traditional applications are designed for humans to input data. AI really flips that on the head, the emphasis moves from the UI or front end application to the database and making it as efficient as possible for AI agents to work with." How Couchbase aims to differentiate in an increasingly crowded database market As has been the case in the database market for decades, there is a healthy amount of competition. Just as NoSQL database capabilities have become increasingly common, the same is now also true of vector database functionality. NoSQL vendors such as MongoDB, DataStax and Neo4j, as well as traditional database vendors like Oracle all have vector capabilities today. "Everyone has vector capabilities today, I think that's probably an accurate statement," McDonough admitted. That said, he noted that even before the new Capella AI services, Couchbase does aim to have a somewhat differentiated offering. In particular, Couchbase has long had mobile and edge deployment capabilities. The database also provides in-memory capabilities that help to accelerate all types of queries, including vector search. Couchbase is also notable for its SQL++ query language. SQL++ allows developers to query and manipulate JSON data stored in Couchbase using familiar SQL syntax. This helps bridge the gap between relational and NoSQL data models. With the new Capella AI services, SQL++ functionality is being extended to make it easier for application developers to directly query AI models with standard database queries. Mohan Varthakavi, VP of Software Development, AI and Edge at Couchbase explained to VentureBeat that AI functions enable developers to easily execute common AI functions on data. For example, he noted that an organization might already have a large volume of data in Couchbase. With the new AI functions, the organization can simply use SQL++ to summarize data, or executive any other AI function directly on the data. That can be done without needing to host a separate AI model, connect data stores or learn different syntax to execute the AI function. How Capella AI brings semantic context to accelerate enterprise deployments The new Capella AI Services suite introduces several key components that address common enterprise AI challenges One of the new components is the model service which addresses enterprise security concerns by enabling AI model hosting within organizational boundaries. As such a model can be hosted for example within the same virtual private cloud (VPC). "Our customers consistently told us that they are concerned about data going across the wire to foundational models sourced outside," Varthakavi said. The service supports both open source models and commercial offerings, with value-added features including request batching and semantic caching. Varthakavi explained that semantic caching provides the ability to cache not just the literal responses to queries, but the semantic meaning and context behind those responses. He noted that by caching semantically relevant responses, Couchbase can provide more contextual and meaningful information to the AI models or applications consuming the data. The semantic caching can help reduce the number of calls needed to AI models, as Couchbase can often provide relevant responses from its own cache. This can lower the operational costs and latency associated with making calls to AI services. McDonough emphasized that the core focus for Couchbase overall with the new AI services is to make it simpler for developers to build, test and deploy AI, without having to use a bunch of different platforms. "Ultimately we believe that is going to reduce latency operational cost, by keeping these models and the data together throughout the entire software development life cycle for AI applications," he said.