The ecosystem.Ai Sandbox is the essential Platform; with all Business, Data Science and Technologist functionality you need to build your own human-centric interactions.
Use the Sandbox to curate and manage all prediction projects and deployments. Validate, analyse and collect all transactions, interactions and customer response data.
Seamlessly integrate and maintain the Platform Sandbox ecosystem, with cloud storage and prediction deployment into a production environment of your choice.
About The Sandbox
- Access to the full ecosystem.Ai SaaS Platform – The Workbench, Notebooks, Dashboards, Server, and Client Pulse Responder[s].
- The ecosystem.Ai Sandbox comes in four sizes*, and features a clean environment for you to start playing around in.
- Pay as you Predict pricing structure, based on size and usage.
- Create recommenders of all shapes and sizes – from products to engagements and more.
- Build your own experiments, make your own models and configure your own deployments.
- The perfect product to suit any business-based machine learning needs
The Sandbox is packed with goodies to solve any Business problem, provide Data Scientists with an easy-to-navigate environment, and provide Technologists with all the right tools.
What you get
- Full No-Code functionality with the ecosystem.Ai Workbench to:
- Create and edit any project
- Add, edit, ingest and view your own data
- Build and deploy machine learning models
- Create configurations for real-time deployments
- Full Low-Code functionality with the ecosystem.Ai Notebooks to:
- Do all of the above, and
- Test out configurations with Simulations
- View Real-Time results of any project [simulations and deployments] using the ecosystem.Ai Grafana Dashboards
- View and analyse Business tracking based results using the ecosystem.Ai Superset Dashboards
- Run all real-time Behavioral predictions in your chosen production environment, using The Client Pulse Responder
- Links to documentation to help you along your journey
- A Small instance is good for running low computational requirement projects. Such as small customer-base testing, single recommenders, and performing enrichments on small datasets. Specs: 4CPU + 8g RAM + 32 Storage
- A Medium instance is the perfect size for most uncomplicated deployments. Using this you can run accurate real-time deployments and monitor comfortably, perform enrichments on most average sized datasets, and run up to three experiments / recommenders / builds at the same time. Specs: 8CPU + 16g RAM + 128 Storage
- Large instance is better for most above average data science requirements. With the large, you can perform enrichments on almost any sized datasets, and deploy multiple recommenders and experiments at once. Specs: 16CPU + 42g RAM + 128 Storage
Base price here is an estimate, calculated according to a Small instance with 50/50 training and deployment time per month.
For more information, contact our Sales Guru Rob here