TeeBI is a performance-oriented API (component library) to enable data gathering, processing and optionally interacting with machine-learning algorithms.

Data can be created manually by code, or it can be automatically imported from many different sources and formats, like databases, files as csv, json, xml, Excel, etc. both by code or using editor dialogs.

Data can be optionally persisted to native binary files that provide ultra-fast access, as each column or field is directly stored from a simple array in a single operation. Millions of rows take few instants to load, sort, aggregate or traverse.

Basic summary features like filtering, sorting, expressions, aggregations and multiple group-by consolidations can be done using simple classes and/or visual editor dialogs. No sql is required, but it is supported.

Integrations with the "R" Language and Python's frameworks provide an easy way to use TeeBI data with statistical and machine-learning algorithms and perform statistical and predictive analysis to help identify patterns and trends.