AI is Thirsty for More Price/Performance

Artificial Intelligence (AI) consumes an enormous amount of computation which leads to enormous consumption of power and water. Many AI techniques represent data as points in N-dimensional space. As large language models (LLMs) are trained, the meaning and context of portions of the text are fit into these N-dimensional spaces. Today's data management platforms aren't even good at low-dimensional data. The reason is the underlying computer science of indexing and query. Craxel's breakthrough O(1) algorithms dramatically improve indexing and querying multi-dimensional data. This has significant impact on the performance and efficiency of various aspects of AI.

Cube

Black Forest is the Fast and Scalable Foundation for Data and AI

Craxel's breakthrough algorithms index data with an entirely unique approach, taking vector embeddings and indexing them at line speed.

  • Vector embeddings are high dimensional objects and can be indexed with Craxel's O(1) algorithms
  • In-memory computing over trillions of vector embeddings is too costly and inefficient
  • With Black Forest, vector embeddings can be organized in hyperscale storage and queried with minimal computation
  • Black Forest can connect the dots between vector embeddings and time series graphs

Time Series Graph Meets AI: Connecting the Dots At Any Scale

The world is composed of trillions of people, places, and things with interconnecting timelines. The digital world is even larger. Many large-scale data problems have objects consisting of timelines with multiple different event types as well as interconnections (relationships) with other objects.  Craxel's breakthrough algorithms enable massive quantities of information to be organized as these time series graphs.

  • Massive quantities of data can now be organized at line speed in a way that facilitates connecting the dots
  • Fuse multiple data types and data sources into a single time series graph as the data is ingested
  • Store petabyte-scale time series graphs in hyperscaled storage
  • Queries across trillions of data points are extraordinarily fast and take very little compute
  • AI models can be trained using timelines and relationships in time series graphs
AI Time Series Graph
Zero trust security

Black Forest Delivers a New Paradigm for Data Security and Privacy for AI

There are significant security and privacy challenges facing the wide-spread adoption of AI in the enterprise. Black Forest provides a built-in zero trust architecture for keeping data secure and compartmentalized.

Black Forest also provides a high-performance searchable encryption capability. High-performance searchable encryption allows every record stored in Black Forest to be encrypted at the application-layer, and Black Forest never needs the encryption keys to operate. This means that Black Forest can't look inside any of the records since it doesn't have the keys to decrypt the records. Yet, queries are still incredibly fast. This is due to the power of Craxel's O(1) breakthrough.

Between security labels on every record, mandatory access controls, attribute-based access control, and high-performance searchable encryption, Black Forest enables customers to achieve pervasive compartmentalization of information. This is crucial to building a strong security model for AI.