Memgraph 3.0 Delivers Streamlined Way to Build Enterprise-Specific GenAI and Agentic AI

• GraphRAG incorporates the right context to take your LLM from generic to useful, as well as personal and enterprise specific

• Upgraded version of the core Memgraph platform makes simplifying and optimizing LLM deployment and knowledge retrieval effortless for organizations of all sizes

• Combination of GraphRAG, dynamic algorithms, and vector search creates market-unique power and functionality for the creation of chatbots and agents

Memgraph, the leader in open-source in-memory graph databases purpose-built for dynamic, real-time enterprise applications, announced a major expansion to its technology stack that will make it even easier for teams to build highly-accurate, real-time AI solutions powered by graph technology.

“With Memgraph 3.0, it’s never been easier to build AI applications”

Memgraph 3.0 enables firms to make their data GenAI-ready and create applications, such as chatbots or agents, more-performant and easier with enterprise-specific outcomes that are accurate, secure and real-time and faster to deliver value. This is achieved through its integration of advanced data retrieval techniques and the full utilization of graph technology’s inherent capabilities—delivered with a level of integration and ease of use that outpaces any other knowledge graph solution currently available.

By integrating vector search, Memgraph combines the creative power of LLMs with the precision of knowledge graphs, enabling richer semantic search insights. GenAI applications powered by 3.0’s standout feature, Retrieval-Augmented Generation in graph (or GraphRAG), enhance reasoning, reduce hallucinations, and work securely within an enterprise’s unique context and data.

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Commenting on the milestone Memgraph 3.0 represents, the company’s CEO, Dominik Tomicevic, says, “For the AI developer, Memgraph 3.0 addresses all the limitations of LLMs (large language models), like hallucinations and inability to keep up with business change.”

Tomicevic explains that LLMs disappoint the enterprise market due to their inherent architecture, which relies on rigid probabilistic frameworks. He highlights that updating the base model with new data is both computationally expensive and impractical, making it a significant limitation for businesses.

With Memgraph 3.0, business users can quickly create knowledge graphs that enhance LLMs, while preventing the accidental exposure of proprietary information, safeguarding an organization’s IP.

According to Gartner® in its Hype Cycle^TM For AI in Software Engineering, 2024 report: “RAG techniques in an enterprise context suffer from problems related to the veracity and completeness of responses caused by limitations in the accuracy of retrieval, contextual understanding, and response coherence. KGs (Knowledge Graphs), a well-established technology, can represent data held within documents and the metadata relating to the documents. Combining both aspects allows RAG applications to retrieve text based on the similarity to the question and contextual representation of the query and corpus, improving response accuracy.”

In practical terms, Memgraph 3.0 addresses the challenge of ensuring prompts generate reliable answers—not by overloading the context window with information, but by enabling the system to navigate the internal knowledge graph. Instead of merely referencing similar user-generated questions, it guides the system to pinpoint the network locations where probable answers reside.

Memgraph 3.0 introduces its unique dynamic algorithms, tailored for real-time data analysis and high-throughput use cases. These enable fast, continuous responses to incoming data without requiring LLM retraining.

Memgraph already powering cutting-edge generative AI deployments across multiple sectors

Many organizations, from mid-size firms to Fortune 100 companies, are leveraging Memgraph’s database and AI support. For instance, Cedars-Sinai uses Memgraph to power AlzKB, a knowledge base for Alzheimer’s research, while Precina Health integrates real-time patient data for personalized diabetes care.

The next step in AI

“With Memgraph 3.0, it’s never been easier to build AI applications,” concludes Tomicevic.

“It’s all bundled, off the shelf, and open source. Developers can dive in without hesitation and start creating chatbots and AI agents today.”

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