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Our mission is clear: to empower organizations with tools that make their data actionable, accurate, and seamlessly integrated into advanced AI workflows. With FalkorDB’s GraphRAG capabilities, businesses can confidently deploy LLM-based applications that meet their needs for precision, speed, and scalability.

FalkorDB was founded to address a critical challenge in deploying large language model (LLM)-based applications: the lack of trust and reliability in existing solutions. Enterprises often struggle with these issues, as even leading vector and search database technologies fail to deliver the high accuracy required for enterprise-grade applications. For instance, Microsoft’s “hybrid+Semantic Ranker” achieved only 75% accuracy as of September 2023—a level insufficient for many business use cases. Our approach is grounded in cutting-edge research and practical innovation. 

In 2023, several academic studies highlighted that Retrieval-Augmented Generation (RAG) systems perform best when paired with Knowledge Graphs, an approach termed GraphRAG. This insight resonated with us, given our expertise in building a low-latency graph database that excels in speed and scalability. FalkorDB leverages GraphRAG technology to enhance LLM performance by integrating external knowledge sources into a structured Knowledge Graph. This enables models to retrieve high-quality, contextually relevant information before generating responses, bridging the gap between generative AI capabilities and the structured or unstructured data enterprises rely on.

To simplify adoption, FalkorDB automates the transformation of organizational data into a Knowledge Graph—a process that is traditionally complex and resource-intensive. This automation allows organizations to manage internal data effectively while incorporating external knowledge for better decision-making and more reliable AI-driven interactions. Our proprietary graph database architecture is uniquely designed for ultra-low latency, using sparse matrix representations and algebraic querying techniques to ensure fast, accurate results.

FalkorDB was founded in 2023 by Guy Korland (CEO), Roy Lipman (CTO), and Avi Avni (Chief Architect)—all former Redis executives with deep expertise in high-performance databases. Their shared vision combines decades of experience in database design with a commitment to solving real-world problems in the era of big data and machine learning.

The market potential is significant. FalkorDB operates at the intersection of two rapidly growing sectors: the graph database market, valued at over $3 billion with a projected annual growth rate of 21.9% through 2030, and the generative AI market, which exceeded $200 billion in 2023 and is expected to surpass $1 trillion by 2030. By addressing key challenges such as “hallucinations” in LLMs and the inability to incorporate organizational knowledge into model outputs, FalkorDB provides a robust solution for enterprises seeking reliable AI integrations.