Watsonx Assistant now provides conversational search, producing conversational answers based on business-specific material to address queries from customers and staff. Conversational search employs generative AI to relieve human authors from manually composing and updating replies; this reduces the total cost of ownership of virtual assistants and speeds up time to value.
For training, deploying, and managing foundation models, IBM watsonx Assistant connects to watsonx, an enterprise-ready AI and data platform from IBM. This allows business users to automate precise, conversational question-answering with specialized watsonx large language models.
Since 2020, IBM and Watson Assistant have used foundation models to analyze and understand text at an advanced level, including customer discussions. Retrieval-augmented generation (RAG), a generative AI architecture that responds to natural language questions with contextual answers based on pertinent, enterprise-specific information, is now being implemented by Assistant through a connection to Watsonx.
Generation with enhanced retrieval (RAG)
RAG is a framework for artificial intelligence that combines search with generative intelligence to find enterprise-specific data in a search engine or vector database and then provide a conversational response based on that data.
Recovery stage
First, Watsonx Assistant extracts pertinent data from the content of your company. Your content might be kept in a knowledge base or content management system, for instance. When a prospect, customer, or employee asks a question, Assistant uses a search tool to connect to this content and retrieve correct, current answers.
From no-code to low-code to custom configuration, IBM Watsonx Assistant enables a variety of patterns to connect to the content of your company. With Watson Discovery for search, Assistant enables an out-of-the-box, no-code integration. Non-technical business users can upload documents, browse the web, or connect to content kept in Microsoft SharePoint, Salesforce, or Box using Watson Discovery.
Additionally, customers can benefit from watsonx Assistant’s startup kits, which detail how to connect to popular search tools like Coveo, Google Custom Search, Magnolia, and Zendesk Support step-by-step.
Stage of answer creation
Watsonx Assistant pulls pertinent data from the content of your company and feeds it into a watsonx large language model (LLM) to provide a conversational response based on that data.
Watsonx Assistant makes sure that the LLM’s replies are based on a confined domain of enterprise-specific content rather of an open domain of internet-scale data by passing it accurate, current content to utilize to construct its answer. The LLM is less likely to “hallucinate” false or misleading information as a result.
Additionally, this approach guarantees that Watsonx Assistant can track each generated response back to its original content. Any client can view the source of a response, as well as their prospects, customers, or staff members. The virtual assistant may display the generated response alone together with references to or extracts from its sources.
Watsonx Assistant has collaborated with IBM Research and watsonx to create customized watsonx LLMs that specialize in producing replies based on enterprise-specific content to enable answer production. Today, clients may set up retrieval-augmented generation for conversational search utilizing step-by-step starting kits that guide them through the full configuration process. Using the watsonx Assistant custom extensions framework, clients can additionally connect to their own watsonx LLMs or those of other parties, both for retrieval-augmented generation and other generative use cases.
Practice of conversational searching
What are the implications for designing, implementing, and maintaining virtual assistants of conversational search, driven by this retrieval-augmented generation framework?
It’s considerably simpler to create and use your own virtual assistant. Watsonx Assistant can accurately respond to a wide range of queries using conversational search without the need for non-technical business people to manually write the answers. Teams can start up and launch a new virtual assistant connected to their organization’s current knowledge base without any human authoring, or they can extend the scope of an existing virtual assistant to cover a new set of topics.
Virtual assistant maintenance also takes less work. Watsonx Assistant automatically gathers data from a knowledge base once it is connected for conversational search in order to inform the generated answers. Teams may easily update the information in their knowledge base when information changes or new information becomes available. The new data will be automatically retrieved by IBM Watsonx Assistant and used to inform its responses. Teams are no longer required to retrain models or manually change replies.
Together, conversational search reduces the effort needed and speeds up time to value for teams wishing to create and implement outstanding conversational experiences with Watson Assistant.
Why use Watsonx Assistant for conversational search?
Building on the base of its prebuilt integrations, low-code integrations framework, and no-code writing experience, IBM Watsonx Assistant’s conversational search feature. Conversational search enables both developers and business users to automate question-answering, freeing them up to create integrated digital experiences and higher-value transactional processes with their virtual assistants.
Beyond conversational search, Assistant continues to work with watsonx and IBM Research to create specialized watsonx LLMs that excel at classification, reasoning, information extraction, summarization, and other conversational use cases. With the help of big language models, Watsonx Assistant has already made significant strides in its capacity to comprehend clients with less effort.
Watch this space for more information on the generative AI capabilities of the IBM Watsonx Assistant. Click the button below to request a consultation if you’d like to learn more about how you can use conversational experiences driven by generative AI to engage your prospects, customers, and staff.
[…] and home delivery simpler than ever. Video chatting with faraway family and friends is simple. AI assistants can play music, make calls, and recommend the best Italian cuisine within 10 miles using voice […]
[…] for Agents: Generative AI is crucial to fast delivering tailored services when your customer care personnel interact with […]
[…] in space AI Ubotica Technologies has partnered with IBM to use watsonx.ai components and IBM cloud infrastructure, with the goal of making it easier for developers to get their […]
[…] re:Invent will include IBM Watsonx a data and AI system, safety features, and adaptive AI advice […]
[…] risk and controls across the enterprise. Visit booth #5006 at NRF to see a demo and learn how Watsonx can improve your store’s operations, customer engagement, and […]
[…] launch of a Center of Excellence (CoE) for the Watsonx generative AI platform has been announced by NTT DATA Business Solutions and IBM. The joint CoE’s main goal […]
[…] businesses. Through this engagement, Korea Quantum Computing (KQC) customers will be able to use IBM Watsonx and advanced AI infrastructure to train, optimize, and implement advanced AI models. Furthermore, […]