Foretify Toolchain Overview
The Trusted Development Toolchain
for AI-Powered AV Stacks
Foretellix’s Foretify data-automation toolchain maximizes and enriches the data for scalable, efficient, and safe development of AI-powered autonomous vehicle (AV) stacks. It enables data-driven training and validation by curating real-world and synthetic data, and augmenting it with hyper-realistic variations and synthetic scenarios to accelerate the development of AI-powered AV stacks.
The Complete Data Automation Toolchain
Foretify Evaluate
Automatically unify, curate, and cleanse both real-world and simulation data to reveal critical coverage gaps and hidden bugs.
Intelligent data curation for training/validation
Scenario search and prioritization
Performance, quality & safety evaluation
Unified ODD coverage metrics
Visual debugging and anomaly triage
Drive scenario variation and generation with physics-based sensor simulation
Foretify Generate
Generate realistic and varied synthetic scenarios to train and test your AV stack across diverse vehicle and VRU behaviors, geographies, conditions, and edge cases.
Physics-based synthetic sensor simulation
Closed-loop and reactive simulation
Real-world log variation and enrichment
Automated scenario generation at scale
Edge case generation and unscripted testing
Intelligent data curation and analysis from real-world drive logs.
Scalable and Seamless
Scalable and
Seamless
Foretify is an open platform – compatible with industry-leading simulators
Architected for large-scale deployment in the cloud or on-premises
Native support for OpenSCENARIO DSL – ensuring formal, reusable, and consistent scenario definitions across workflows
Integrated with NVIDIA Omniverse and Cosmos for hyper-realistic sensor simulation and scenario generation
Integrated with Mathworks Roadrunner for concrete scenario design and generation
Ready to accelerate your journey to AI-powered autonomy?
