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LynxKite - The Complete Graph AI Platform

LynxKite is a powerful open-source analytics tool built by Lynx Analytics for very large graphs and other datasets. It effortlessly helps reveal hidden network properties and detects unknown clusters in otherwise dormant raw data.


How LynxKite is Being Used


Include LLM text embeddings to enable Graph RAG and Machine Learning


Transform text into a feature vector and compute embeddings for string attributes on nodes or edges using OpenAI models or open-source models


Predict what can be learned or concluded from a text. For example, predicting surgeries based on medical transcripts or determining sentiment based on chat history

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Gene expression analysis to identify potential therapeutic targets


Automatically generate graphs that map to specific properties (e.g. protein to protein interactions)

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Perform correlation analysis and simulate changes to understand impacts

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Route optimization for transport and logistics companies


Make routing decisions

based on cost/benefits outcomes


Integrated Graph AI optimization function based on multiple parameters

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Large-scale network planning for telecoms


Build and explore possible cable routes using third-party geo data


Advanced functions such as Prize Collecting Steiner Trees to determine optimal network layout

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Product recommendation for upsell and cross-sell for e-commerce vendors


Leverage existing customer data and catalog



Perform affinity analysis to determine next-best

offer or action

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From Graph Discovery to Visualization, To Graph Al: A One-Stop Shop

LynxKite helps analytics teams transform data into graphs and let users perform advanced analytics, regardless of their proficiency level with graphs and data science. It is the ideal tool for enterprises that want to experiment with Graph Al analytics, minimize the learning curve, and accelerate' proof of value.


Main Features

  • Import data (from MB to TB) from a variety of sources by working directly with traditional data sources or graph databases
  • Use algorithms from a large library of graph operations, including Graph AI operations
  • Put together complex data processing pipelines where you can combine graph operations, classical data analysis operations, and machine learning
  • Experiment with different approaches by discovering graphs and interpreting algorithm results at any step of the calculations, and tuning parameters
  • Combine the benefits of a friendly "no code" GUI as well as coding via a powerful Python integration (code embedding, Python API, code generation)
  • Scale to billions of edges thanks to the Apache Spark cluster computing engine and the NVIDIA cuGraph GPU-accelerated algorithm library

Our Technology Partners

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New 2

By Popular Demand

To make it easier for our growing base of dedicated and enthusiastic users, the latest version of LynxKite uses the industry-standard Apache License 2.0, providing a familiar licensing framework and allowing companies to use LynxKite without necessarily sharing their modifications. You can download LynxKite 5.4 here.


Combining Graph and Text Embeddings with LynxKite

LynxKite supports several operations to help construct a feature vector (such as Embed vertices and Bundle vertex attributes into a vector) and operations to train models on these vectors. With the advent of language models, turning text into a feature vector has become a powerful tool. We have added support for this in the recently released LynxKite 5.4. 

Talk To a Graph Specialist

We offer tailored consulting services to implement LynxKite in your analytics environment and accelerate the learning curve. Having developed LynxKite, we are in the best position to help you learn how to use graph AI analytics to achieve your goals.