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Smart Data Quality & Auto-Fix
Raw Signal. Issues Detected. Perfectly Cleaned.
Event Detection & Labeling
Every Event & Maneuver. Detected Automatically. Labeled Instantly.
Simplicity and flexibility win
01
Upload &
Map Signals
Load your dataset and match your signal names to a standardized schema. DataPilot suggests mappings automatically – you review and confirm.
02
Check Data
Quality
Automated checks run across every signal and flag issues with full detail – so you know exactly what failed and why.
03
Inspect & Fix
Drill into any signal, select a fix method, and preview the corrected result against the raw data before applying anything. Fix them in one guided session.
04
Label Events
Driving events and maneuvers are detected automatically. Just review the results.
05
Export
Get a validated, labeled dataset ready for your calibration or AI workflow.
Watch On-Demand Webinar: DataPilot Demo
Designed for teams working with vehicle time series data:
Vehicle Dynamics Engineers
Validate every measurement campaign instantly – no more discovering sensor errors days later.
Calibration & Validation Teams
Trust your reference measurements. Automated checks ensure signal reliability before you invest time in calibration.
Data Scientists & ML Engineers in automotive R&D
Train better models faster. Clean, event-labeled datasets with balanced splits across road surfaces and maneuvers.
Plans for teams of all sizes
Choose the plan that fits your team’s needs, with powerful tools to automate data preparation, improve data quality, and accelerate AI-driven vehicle development.
DataPilot S
The essentials to provide you with stress-free data processing.
DataPilot M
Accelerate every step from raw vehicle data to AI-ready insights.
DataPilot Enterprise
Tailored to your users, data volume and deployment needs.
Get Free Access
Create your DataPilot account and explore the product for free for 30 days
FAQ
Data preparation is unavoidable – but not all of it needs to be manual. The most time-consuming parts, like hunting for quality issues across hundreds of signals or building driving context from raw logs, can be handled significantly faster. DataPilot takes the tedious, repetitive work off your plate so your engineers can focus on the analysis itself.
DataPilot includes an automated matching step that maps your own signal names to a standardised schema. You can override suggestions manually.
You don’t have to. Every flagged issue shows what was detected and why it was flagged. Before any fix is applied, you see a preview of the corrected signal alongside the original. Nothing changes in your data without your explicit confirmation, and your raw files are never touched – cleaned output is always a separate version.
DataPilot detects driving events – braking, acceleration, cornering, and driving context such as road type and conditions – automatically from the signal data. Results are reviewable per trip before you export anything. The detection logic is transparent: thresholds are visible, not hidden inside a model.
On-premise and data-lake deployment is available for enterprise customers. Reach out directly to discuss deployment options for your organization.
DataPilot is built for the engineers who work directly with vehicle data – data scientists, test engineers, calibration engineers, and ML engineers who currently spend time writing scripts to clean and validate datasets before analysis.
You can use DataPilot free for 30 days. When the trial ends, a paid subscription is required to continue using the platform.
- DataPilot S — €15,000 per year: Includes five user licences and up to 300 GB of uploads per month. Additional user licences are available for €2,000 per user per year.
- DataPilot M — €50,000 per year: Includes 25 user licences, up to 1 TB of uploads per month and increased computing performance.
- DataPilot Enterprise — Custom pricing: A tailored package based on your required number of users, data volume, computing performance and deployment setup. Deployment options include a customer-managed VPC or a dedicated single-tenant private cloud.
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