Our Mission

To equip robot manufacturers with AI-powered tools that independently assess reliability, uncover hidden issues, and enhance performance, promoting responsible oversight and wider adoption of safer autonomous systems.

Who is this documentation for?

• Robotics developers and engineers integrating Ridescan AI with their robots
• Fleet managers and operators seeking performance analytics and risk monitoring
• System integrators building custom workflows or dashboards using Ridescan API

Key Capabilities

• Comprehensive Reporting & Insights: Monitor risk scores and performance metrics for all jobs performed by your robots.
• Unified Data Aggregation: Manage and monitor multiple robots across various sectors from a single platform.
• Seamless Integration: Supports a wide range of robotic systems and provides robust API endpoints for integration.
• AI-Driven Anomaly Detection: Automatically detect and report anomalies or reliability issues.
• Scalable & Secure Architecture: Growth without compromising security.

Requirements

• Access to the Ridescan AI platform (sign up required)
• API credentials for programmatic access
• Supported robots: Industrial arms, mobile platforms, drones, quadrupeds, humanoids

Architecture Overview

• Cloud Platform: Centralized processing, analytics, and dashboard
• API Layer: RESTful endpoints for integration, data ingestion, and retrieval
• Device Connectors: Lightweight agents or SDKs for robot-side integration

Next Steps

• Getting Started Guide: Learn how to set up your account, connect your first robot, and make your first API call.
• Examples and Use Cases: Step-by-step guides for common integration scenarios.
• FAQ: Explore detailed API endpoints and data models.