Artificial Intelligence Powered By Knowledge Graph

Accelerate Time To Production, And Deliver Better Results!

Increase Context For Machine Learning With Graph

DataWalk can be utilized as a machine learning platform that enables you to quickly integrate,link and analyze all your internal and external data in a business representation through connections between business entities, processes, and events. Strong knowledge graph and LLM foundation allows you to derive new insights and patterns from vast amounts of existing data and metadata quicker than ever. DataWalk embeds AI machine learning to automatically complete, clean, overwrite, fix and enrich data so that it can quickly be used for further analysis.

Collaboration At The Enterprise Level

The knowledge graph interface allows data engineers, data scientists and citizen data scientists who are less technical to collaborate and accelerate results from machine learning. This fosters faster results from AI and machine learning without the need for separate workflows. It's a platform that makes the power of AI including generative AI / large language models (LLM) accessible to everyone involved in the process.

Automated Data Engineering Pipeline

With DataWalk’s) capabilities you do not need to think about maintaining dozens of ETL tasks created from hundreds of lines of code. DataWalk is designed to support an entire enterprise data processing pipeline, automating it in the most optimal way, such that you can eliminate the need for further optimization regardless of whether it’s feature generation or any other data manipulation.

Jupyter Notebook Interface for AI, ML and GenAI (LLM)

With DataWalk you can access your knowledge graph via the Jupyter Notebook interface*, which enables you to create a sandbox with a separate data model for AI and machine learning usage. This allows for experimentation with various LLMs and standard or graph machine learning algorithms on large datasets.

Instant Feedback Loop for Superior Results

Fast feedback is critical to effectively tune models, and with DataWalk fraud detection machine learning capabilities, the feedback loop is immediate and based on real data. This accelerates model improvement, ensuring better, faster results in any AI and machine learning application.When your models are deployed, then feedback is automatically captured. Better, faster feedback helps enable superior results.By leveraging graph RAG , DataWalk enhances how businesses utilize generative AI and LLM technologies, making AI more accessible and effective across various industries.

Use Cases For DataWalk AI/ML

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