AI Development Platform-AI App Design-4Paradigm Sage

Industry Leaders Choose 4Paradigm

Advantages

Effective adoption

Based on home-grown large-scale machine learning computing framework and live components, precisely get value from massive data, respond to front-end business needs in real time, and build closed-loop data flow to support continuous iterative improvement of models.
Low barrier to automation

Support enterprise-wide multi-table modeling with the full-process AutoML solution, outperforming 90% of data scientists in top machine learning competitions.
Full scenarios coverage

Support multiple modeling methods such as DAG, Notebook and Auto for full-stack scenarios like ML (decision making), CV (vision), NLP (text), and Speech (voice).
Flexibility and adaptability

Help users custom development and integration in a fast and cost-effective manner; enable unified management of platform-based development models and external models; and fully support mainstream open-source frameworks and algorithms.
Low TCO

Manage plenty of high-dimensional machine learning algorithms for various scenarios, outperforming computing frameworks like Spark in rapidly computing massive data for machine learning; safeguard your AI adoption with near-linear growth in computing efficiency.

Features

AI-oriented data governance

Data quality determines the effectiveness of data model. 4Paradigm Sage Studio delivers AI-oriented data governance to help you collect actual data, guarantee the chronology, closed-loop and consistency features of data, and significantly improve data governance.
Flexible outcome-based modeling

Home-grown core computing framework and algorithms:
With 4Paradigm’s self-developed large-scale machine learning computing framework GDBT, support up to 1 trillion (1012) dimensional feature, significantly improving model effectiveness and training performance.
Full-stack AI scenarios and diversified modeling:
Support AI scenarios like ML (decision making), CV (vision), NLP (text) and Speech (voice), and enable diversified modeling such as DAG (drag-and-drop visualization), Notebook and Auto (with intervention and parameter tuning).
Custom operator development platform:
Based on Studio Operator Development Platform, custom development and integration in a fast and cost-effective manner to realize unified precipitation and application of AI operators.
Unified and comprehensive model management

Unified model management:
Enable unified management of platform-based development models and external models; support model sorting by evaluation indicators, storage occupancy and creation time; and allow model filtering by source, type and algorithm dimensions.
Comprehensive model evaluation:
Provide related assessment and interpretation reports in the model management tool, including model indicator report (Logloss and AUC), feature importance report and model structure analysis.
Simple and easy app building

Following model training via Studio modelling IDE, you can build, orchestrate, debug and package AI application with Studio application IDE. You can turn models into application via visualized form configuration or coded parameter editing to deliver applications for front-end business systems.
Rapid deployment and reliable application control

Integrated AI app management platform:
Enable rapid deployment as well as complete, reliable and flexible enterprise-level AI application management, helping you go live and run AI applications as needed.
Continuous improvement of model effects:
Based on HyperCycle methodology, build closed-loop data flow to iteratively optimize models with actual data from front-end business systems, and help you adapt to ever-changing market by continuously improving model effects