PredictSense

PredictSense, developed by Winjit Inc, is an end-to-end Machine Learning platform powered by AutoML that aims to enable businesses to create AI-powered analytical solutions. According to the vendor, PredictSense is designed for enterprise-level organizations and targets data scientists, business intelligence teams, project managers, and professionals in the banking industry. With its user-friendly interface and advanced features, PredictSense aims to accelerate machine intelligence and contribute to the technological revolution of tomorrow.

Key Features

AutoML: According to the vendor, PredictSense automates the process of building ML models and offers ML project management capabilities. It aims to enable users to create ML models without extensive coding by providing a user-friendly interface for building and managing ML models.

Explainable AI: PredictSense offers visual explanations for model predictions, according to the vendor. This feature aims to help users understand how the model arrived at a particular prediction, providing transparency and interpretability in AI-driven decisions. It is designed to enable users to trust and validate the model's outputs.

MLOps: PredictSense manages end-to-end ML pipelines, according to the vendor, streamlining the deployment and monitoring of ML models. It aims to ensure efficient collaboration and governance of ML projects, facilitating the sharing and exporting of ML projects.

Click and Code: According to the vendor, PredictSense allows users to write custom code for data analysis and preparation. It provides flexibility for advanced users to customize their ML workflows and integrates with popular programming languages like Python and Jupyter notebooks. This feature supports code-driven ML development for more complex projects.

Automated Model Deployment and Monitoring: PredictSense enables one-click deployment of ML models to production environments, according to the vendor. It provides automated monitoring of model performance in real-time, detecting data drift and identifying performance degradation. This feature aims to facilitate retraining of models to maintain optimal performance.

Data Preparation with Ease: According to the vendor, PredictSense connects to various data sources for data loading and handles missing values and outliers with different imputation strategies. It provides advanced visual reports for exploratory data analysis and supports data transformation and extraction from various formats like PDF and HTML.

Model Training Automatically: PredictSense offers a wide range of pre-built ML algorithms for model training, according to the vendor. It aims to facilitate feature engineering to optimize model performance and performs hyper-parameter tuning to fine-tune model accuracy. This feature supports parallel model training for faster results.

Evaluate on Various Criteria: According to the vendor, PredictSense provides a leaderboard for model comparisons and generates industry-standard metrics for model evaluation. It offers visualizations like performance plots and confusion matrices, allowing for quick prediction and what-if analysis.

Deploy to Production with 1 Click: PredictSense utilizes a dockerized toolkit for easy deployment of ML models, according to the vendor. It supports deployment to any production environment and detects and alerts on data drift for performance maintenance. The vendor claims it enables retraining of models to keep them up-to-date.