Overview

Sonatus Collector AI is an AI-enhanced vehicle data collection solution for OEMs and fleets that enables precise, dynamic capture of in-vehicle signals and media across the entire vehicle lifecycle. Using lightweight, policy-based collection rules that can be authored via a GUI or APIs, Collector AI lets teams trigger and tune data capture in real time — from pre-production and testing to post-sales diagnostics and fleet telemetry — while protecting privacy and minimizing bandwidth and storage costs. The product supports thousands of signal types (CAN, ECU diagnostics, logs, media captures, network stats), fine-grained triggers (signals, geofences, schedule, power state), and secure transmission and storage; it also integrates generative AI to simplify policy creation and broaden access to vehicle data for multiple OEM groups.

Features and Capabilities

• Data Types & Coverage: Collects CAN signals, ECU diagnostics, log files, media captures, and network statistics across varied E/E architectures, supporting both passenger and commercial vehicles.
• Dynamic Policy Management: Create, edit and deploy lightweight collection policies in minutes via a cloud console or APIs; policies are small (kilobyte-scale) and can be merged, scheduled, and managed across millions of vehicles without code changes.
• Precise Triggering: Trigger collections on fine-grained events such as specific CAN signals, vehicle power state changes, geofence entry/exit, schedules (time-of-day / day-of-week), and third-party or user-defined events for targeted captures.
• GenAI-Assisted Policy Creation: Uses Generative AI / NLP to suggest and generate collection policies in natural language, streamline selection of relevant signals among thousands, and produce graphical policy representations for clarity and iteration.
• Operational Scale & Campaigns: Manage campaigns and policy rollouts at fleet or global scale, adapt collection scope/duration/resolution on the fly, and support multiple user groups concurrently.
• Cost & Bandwidth Optimization: Lightweight policies and multiple storage/transmission modes reduce upload and processing costs; supports local pre-processing vs. cloud upload decisions to optimize utilization.
• Security & Privacy Controls: Role-based access control, encryption at rest, TLS for transmission, and GDPR/CCPA-style compliance features that allow OEMs to honor driver privacy preferences and select aggregated vs. precise data capture.
• Use Cases Supported: ECU calibration and tuning from real-world data, rapid customer issue diagnosis, fleet analytics (safety, efficiency), ADAS/Autonomy dataset collection and model tuning, and enabling new value-added services and revenue streams.
• Integration & Ecosystem: Works with in-vehicle storage and networking components (e.g., network shared storage and SOA adapters) and has demonstrated integrations with partners/OS vendors (example: a Red Hat In-Vehicle OS integration for gateway ECUs).
• Deliverables & Resources: Offers datasheets and product overview resources (product datasheet describes detailed capabilities and deployment models; demo and resource materials available for evaluation).