Build next-generation AI applications with FalkorDB’s powerful graph database platform
Build next-generation AI applications with
FalkorDB’s powerful graph database platform
By way of design the traditional vector databases you know well, are leaving you and your team stuck. Half truths and inaccurate responses keep your application projects on hold, leading you to circle back again and again.
Built on the most advanced graph database, you’ll ingest the highest volume of data and query it into a knowledge graph that gives you a higher perspective through relational insights – in sub-milliseconds!
Our state of the art technology gives you the freedom to develop applications grounded in your data. No more sweating to keep up with the standard – you set the pace of what is possible, with inbuilt GenAI capabilities previously unimaginable.
Our GraphRAG solution is so fast and light, it allows for more queries at the touch of a button
Allows your knowledge to work for you
With incredible accuracy, say goodbye to half truths and no results
Our GraphRAG solution is so fast and light, it allows for more queries at the touch of a button
Allows your knowledge to work for you
With incredible accuracy, say goodbye to half truths and no results
There is a better way than simply segmenting data into chunks and encoding it into ineffectual vectors.
Now you can feed high volumes of unstructured data through your database at lightening speed, unlike anything you’ve experienced before.
Brilliantly extract the relational information between your data entities, priming it for newfound contextual use.
With our GraphRAG, you can bask in enjoying immediate accuracy.
With information retrieval extracted from the connections between sub-knowledge levels, you’ll receive the most concise, relevant and contextual answer to your query every time.
Unlike vector databases who simply search for the nearest match and provide irrelevant or simply inaccurate results – not answering anything at all.
Now you have the answers you’ve been waiting for.
Semantic results from vector databases that don’t get you anywhere or building much, are a thing of the past.
Now, you can simply ask your database like you would an all-knowing genie, and get something you never expected. Pulling from the accurate, relationally-rich knowledge graph, you’ll receive answers that solve your building dreams.
There is a better way than simply segmenting data into chunks and encoding it into ineffectual vectors. Now you can feed high volumes of unstructured data through your database at lightening speed, unlike anything you’ve experienced before.
Brilliantly extract the relational information between your data entities, priming it for newfound contextual use.
With our GraphRAG, you can bask in enjoying immediate accuracy. With information retrieval extracted from the connections between sub-knowledge levels, you’ll receive the most concise, relevant and contextual answer to your query every time.
Unlike vector databases who simply search for the nearest match and provide irrelevant or simply inaccurate results – not answering anything at all.
Now you have the answers you’ve been waiting for. Semantic results from vector databases that don’t get you anywhere or building much, are a thing of the past.
Now, you can simply ask your database like you would an all-knowing genie, and get something you never expected. Pulling from the accurate, relationally-rich knowledge graph, you’ll receive answers that solve your building dreams.
FalkorDB’s Graph Database excels in source code analysis by modeling relationships between code components such as classes, methods, and dependencies. It enables tracing complex code flows, identifying dependencies across modules, and visualizing the impact of changes. With graph queries, developers can efficiently navigate large codebases, detect code smells, and optimize performance bottlenecks.
FalkorDB is pivotal in security applications by correlating diverse data points like user behaviors, access patterns, and network connections. It enables threat detection by identifying anomalous activities through pattern recognition and graph algorithms. Security analysts leverage graph databases to visualize attack paths, trace incident timelines, and prioritize response actions.
FalkorDB’s Knowledge Graph for Corporate Documents LLM applications offers advanced semantic understanding, enabling precise retrieval (GraphRAG) and analysis of legal texts, contracts, and compliance documents. It facilitates entity extraction to identify key stakeholders, legal terms, and obligations, streamlining due diligence and risk assessment processes.
FalkorDB’s Graph Database excels in source code analysis by modeling relationships between code components such as classes, methods, and dependencies. It enables tracing complex code flows, identifying dependencies across modules, and visualizing the impact of changes. With graph queries, developers can efficiently navigate large codebases, detect code smells, and optimize performance bottlenecks.
FalkorDB is pivotal in security applications by correlating diverse data points like user behaviors, access patterns, and network connections. It enables threat detection by identifying anomalous activities through pattern recognition and graph algorithms. Security analysts leverage graph databases to visualize attack paths, trace incident timelines, and prioritize response actions.
FalkorDB’s Knowledge Graph for Corporate Documents LLM applications offers advanced semantic understanding, enabling precise retrieval (GraphRAG) and analysis of legal texts, contracts, and compliance documents. It facilitates entity extraction to identify key stakeholders, legal terms, and obligations, streamlining due diligence and risk assessment processes.
“As we continue to develop and refine our use of FalkorDB, we are excited to take advantage of its new features, such as Vector Index support, to solve new challenges.”
“As one of earliest adopters of FalkorDB (since early 2019), we chose to base our foundation on best-suited technology core but equally to be surrounded by the support team that is an absolute pleasure to work with.”
“FalkorDB feeds our foundational model algorithms via PyTorch and Tensorflow dataloaders, and is updated with output embeddings from the aforementioned algorithms as well.”
