Marple is a web-based platform designed for the processing, visualization, and analysis of large time series datasets, specifically tailored for engineering teams in sectors like automotive and aerospace. It enables users to quickly identify trends and anomalies in their data through interactive visualizations and automated reporting, enhancing collaboration and decision-making efficiency.
Funding
Funding not disclosed
Founders
Product
Problem
Engineering teams often struggle to efficiently process, visualize, and analyze large time-series datasets generated from testing and R&D activities. Identifying trends, anomalies, and correlations within these datasets can be time-consuming and require specialized tools, hindering data-driven decision-making.
Solution
Marple is a web-based platform designed to streamline the analysis of large time-series datasets for engineering teams. The platform enables users to quickly visualize data, identify trends and anomalies, and generate automated reports. With its interactive drag-and-drop interface, Marple allows users to visualize millions of data points in milliseconds and create calculations across numerous datasets. The platform also facilitates team collaboration through data sharing, annotations, and a centralized workspace.
Target Audience
Marple is primarily targeted towards engineering teams in industries such as automotive, aerospace, energy, and manufacturing, as well as R&D departments dealing with time-series data from complex systems.
Features
- Interactive data visualizations with zoom, select, and pan capabilities
- Support for time series, scatter, map, and frequency plots
- Time series data mining with AI-powered tools for trend and anomaly detection
- Automated report generation with a no-code report editor
- Support for over 10 different file formats, including CSV, MAT, and MDF
- Database connectivity with Time Series Databases such as AzureDataExplorer, TimescaleDB, InfluxDB, and PostgreSQL
- API for automated data uploads
- Team collaboration features, including data sharing and annotations