Our Technology

Data Mining


Models

Our underlying models include decision trees, linear and logsitic regression, FPGrowth and many more

Parameters

Model parameters can be manually tuned or automatically optimised using heuristics

Algorithms

Our bespoke algorithms offload filtering and aggregation onto your data store, minimising data transfer and maximising build speed

Predictions

Predictions can be made in the UI or via a high-performance API.

CI / CD for Data Pipelines

Github Actions
  • Build and maintain Data Mining models directly from your CI/CD pipelines in Github Actions
  • Create cloud data infrastructure for testing or deployment within Github Actions
    • S3, SNS, SQS, Glue Databases, Glue Tables
    • GCS, PubSub
    • Upload data from any URL into S3/GCS
GATE – Github Actions Editor
  • Visual editor for Github Actions
  • Discovery of pre-build Actions
    • Directly from organisations
    • From Github Marketplace
    • From locally provided actions
  • Discovery of available variables and secrets across organisation, repository and user settings
  • Validation of settings prior to making a commit

1. Register data sources

Choose from cloud data platforms like Snowflake, Google BigQuery, Amazon Redshift and more, or upload your own data files

2. Build models

Answer a few simple questions based on your analysis of choice and we’ll do the rest

3. Make predctions

Once a model is built, new predictions can be made in real-time via our high performance API endpoints to surface predictions in your customer facing or backoffice systems