No-code Graph RAG employs autonomous agents to integrate enterprise data and domain knowledge with LLMs for context-rich, explainable conversations
Graphwise, a leading Graph AI provider, announced the immediate availability of GraphDB 10.8. This release includes the next-generation Talk-to-Your-Graph capability that integrates large language models (LLMs) with vector-based retrieval of relevant enterprise information and precise querying of knowledge graphs. This lets non-technical users derive real-time insights and retrieve and explore complex, multi-faceted data using natural language. GraphDB 10.8 also enables the deployment of seamless, high-availability clusters across multiple regions, ensuring zero downtime and data consistency without compromising performance.
By leveraging knowledge graphs for retrieval augmented generation (RAG), organizations can enhance answer quality and augment their proprietary information with machine-interpretable domain knowledge. Graphs help connect the dots across diverse data sources, surface knowledge, and derive competitive insights. This may be why Gartner is putting knowledge graphs at the epicenter of their 2024 Impact Radar right next to Generative Artificial Intelligence (GenAI).
“Graphwise’s latest version of its GraphDB engine enables us to experiment, prototype, and showcase the potential of Graph RAG to deliver accurate, explainable, and replicable research retrieval and insights,” said Gary Leicester, Content Metadata Controller at CABI – an international, inter-governmental, not-for-profit organization that provides information and applies scientific expertise to solve problems in agriculture and the environment. “Leveraging Talk-to-Your-Graph 2.0 technology allows us to demonstrate this potential rapidly and intuitively, paving the way for a production-ready solution.”
Following closely on the heels of the formation of Graphwise — the result of the merger between Semantic Web Company and Ontotext — the latest features provide easy access to complex datasets, allowing agents to deliver nuanced, precise answers in a style that feels intuitive and responsive. Non-technical users can now carry out their data retrieval and analysis tasks instantly, removing the delays and the overheads that occur when relying on data management staff. Users can also easily ask for explanations, evidence, and clarifications to check supporting information and gain confidence in the answers provided.
GraphDB 10.8 reduces the R&D time for GenAI applications by offering a no-code framework based on GenAI-powered agents that intelligently combine multiple retrieval methods to deliver context-rich conversations and reduce non-determinism. To help AI developers fine-tune conversational agents (chatbots), it automatically heals retrieval query errors and provides quick access to the underlying method invocations, results, and error messages.
This new version of GraphDB was designed not only for data scientists, knowledge engineers, and enterprise users working with large knowledge graphs, but also for decision-makers in data-intensive industries such as financial services, manufacturing, and life sciences who rely on sophisticated data insights and need intuitive, conversational access to information. Key features include:
- Knowledge graph-driven conversational AI through intelligent agents: Combining the latest in RAG technology, the solution enables agents to retrieve data in real time and deliver precise and context-rich responses, all within a conversational, AI-driven format.
- Diverse query methods feeding flexible retrieval workflows: Each agent leverages a full range of query methods: SPARQL for structured data, graph embedding-based vector similarity search for focused, open-ended questions, and full-text search for broader open-ended inquiries. This versatility enables agents to interpret and respond dynamically across a wide spectrum of inquiries, from pinpointing related concepts to analyzing extensive datasets.
- Multi-agent personalization with memory: Users can set up multiple agents, each tailored to their specific data and domain-specific needs. With unique instructions and memory capabilities, this enables seamless adaptation to various workflows and data interactions.
“This release of our graph database engine is particularly important because it removes technical barriers and allows users to interact conversationally with data without needing query-building expertise. While we launched an early version of the Talk-to-Your-Graph tool a year ago, the new version offers much more comprehensive query-answering and increases the range of questions that can be answered. What’s even more important, GraphDB 10.8 will massively reduce the time data scientists need to configure and fine-tune a chatbot,” said Atanas Kiryakov, President of Graphwise. “By accelerating access to data, this release lets users conduct advanced searches quickly and accurately across the knowledge graph. As a result, enterprises can scale data interactions across teams while maintaining customizability to meet specific workflow and business requirements.”
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