An operating system for the teams building autonomous and software-defined systems.
SoaringIQ turns engineering requirements, fleet data, and test scenarios into executable validation workflows, with a human in the loop, on infrastructure you control.
Try the platform on real driving data.
Watch the agentic validation workflow in action, then explore SoaringIQ in a live sandbox, no setup, sample fleet data included.
Simple engineering questions should not require days of coordination.
Validation teams are bottlenecked by fragmented context, manual tooling, and slow handoffs, exactly when software-defined systems demand the opposite.
- 01Requirements spread across documents, teams, and suppliers
- 02Engineering knowledge locked in experts' heads
- 03Manual translation of questions into scripts, queries, and test logic
- 04Long feedback loops between function owners, data teams, and validation engineers
- 05Pressure to validate more software-defined functions with fewer resources
Agentic validation, end to end.
A working system that lets engineers move from a question to a verified validation finding, without writing the glue code between them.
- Ask validation questions in natural language
- Convert requirements into structured detection logic
- Run scenario detection on time-series driving data
- Visualize detected events and signal behavior
- Review, annotate, and export findings
- Keep the engineer in control with HITL verification
Focused on ADAS & self-driving validation
Our MVP is built where the pain is sharpest today: scenario-based validation of driver-assistance and autonomous functions on real fleet data. The architecture is built to generalize beyond it.
Engineered for real validation workflows.
Requirement-to-test logic
Convert natural language requirements into executable scenario detection logic.
Data-driven validation
Run automated checks on driving data and surface relevant events, edge cases, and failures.
Human-in-the-loop review
Engineers verify assumptions, approve logic, annotate findings, and stay in control.
Integrates with your stack
Connects to existing data pipelines, databases, dashboards, and engineering workflows.
An agentic OS for validation and system engineering.
We're moving from a focused MVP toward a broader AI-first platform , one that scales engineering intelligence across autonomous system development.
- 01Multi-agent validation workflows across requirements, data, test logic, and reporting
- 02AI assistants for function owners, validation engineers, data analysts, and system engineers
- 03Integrations with enterprise data platforms, simulation tools, issue trackers, and requirement systems
- 04Small domain-specific models for cost-efficient enterprise deployment
- 05Private / on-premise deployment for sensitive automotive and industrial data
- 06Expansion from ADAS to drones, trucks, industrial robots, and other autonomous systems
The validation gap is widening.
Software-defined everything
Vehicles and machines are becoming software-defined, multiplying the surface area to validate.
Complexity outpaces headcount
Validation complexity is growing faster than engineering teams can scale.
Traceable validation
OEMs and suppliers need cheaper and more auditable validation workflows.
Domain-aware AI
Generic AI tools fall short. Industrial teams need systems built for their domain.
Built from real validation experience.
SoaringIQ is founded by an engineer with 8+ years of hands-on ADAS and data-driven validation experience across Tier-1 and Volkswagen Group environments. The product is not a generic chatbot, it is built around real engineering workflows, real validation pain points, and enterprise constraints.
Building the AI layer for validation engineering.
We're speaking with automotive and autonomous system teams who want to reduce manual validation effort and accelerate engineering decisions.