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HyperPilot

Paid

An artificial engineering super-intelligence for control software

4.5
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Type
Saas
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About HyperPilot

HyperPilot is an artificial engineering super-intelligence platform designed specifically for control software development. It consists of three one-shot AI engines — Req.Gen, Test.Auth, and SW.Syn — that transform a controls-engineering project from high-level intent into production-grade software without iterative chat. Req.Gen generates a complete system architecture and fully decomposed traceable requirements from inputs like prompts, data sheets, standards, or legacy code. Test.Auth automatically authors executable test suites that exhaustively verify every requirement, supporting SiL, HiL, bench, and product-level testing. SW.Syn, powered by a proprietary algorithm-discovery foundation model, discovers a control algorithm guaranteed to pass 100% of the test suite with no human-in-the-loop. The platform eliminates months of manual work by automating the V-model of controls engineering, while keeping stakeholder intent and acceptance testing under human control.

Key Features

Req.Gen: generates system architecture and fully decomposed traceable requirements from prompts, data sheets, standards, or existing code
Test.Auth: authors complete executable test suites that exhaustively verify every requirement across SiL, HiL, bench, and product levels
SW.Syn: discovers a control algorithm using a foundation model that searches algorithm space directly, guaranteed to pass 100% of the test suite
One-shot AI engines: structured input in, structured output out – no chat or back-and-forth required
Automates the V-model of controls engineering, reducing months of work to a final pass of approval
Arms with human review for requirements and tests, full automation at the implementation node

Pros & Cons

Pros
  • Dramatically reduces development time from months to a single approval pass
  • SW.Syn guarantees that generated code passes 100% of the test suite without human edits
  • Algorithm-discovery foundation model searches an unbounded space, unlike LLMs limited to public code
  • Enables true test-driven development with automated test suite generation before code synthesis
  • Structured one-shot outputs eliminate iterative chat and reduce ambiguity
Cons
  • Requires structured input formats (specs, standards, requirements trees) – not suitable for casual or natural-language-only tasks
  • Pricing only available via contact, with no transparent starting price
  • As a new platform, may have limited community support and integration examples
  • Full automation on the implementation node may be intimidating for teams accustomed to manual oversight

Best For

Control software development for electric vehicle powertrainsInverter control system design and verificationBattery management system software generationVehicle supervisor control logic synthesisAny safety-critical embedded controls engineering project requiring traceability and exhaustive testing

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