An AI-native platform for high-rigor systems engineering. We turn engineering intent into explainable, certifiable, realizable designs.
Built by engineers from Cruise, Cook Research Inc., and Lab Lens.
Complex systems defeat individual cognitive bandwidth. Not because engineers aren't capable, but because the tooling extracts a "Traceability Tax." Manually linking requirements to components and maintaining audit trails consumes 30% of an engineer's week. Shadow Excel sheets fill the gap because official modeling tools are too slow for real-time reasoning. Our tools eliminate the tax: they autonomously synthesize the design artifact, so engineers can focus on the engineering.
The same graph-theoretic foundation that maps an engineering system can traverse the structure of a scientific problem space. NeuronKite's second category applies autonomous reasoning to hypothesis generation, evidence synthesis, and experimental design. The result is unstructured research context turned into navigable knowledge.
The market is split between fast-and-informal (Excel, whiteboard) and slow-and-rigorous (Cameo, DOORS). Neither side wins. Speed without rigor fails audits; rigor without speed misses milestones. Our tools resolve this tension. A purpose-built graph reasoning engine provides the formal substrate; a frontier AI model provides the synthesis velocity. Conflict detection is algebraic, not heuristic. Every decision has a rationale node. Every claim has a provenance trace. The output is machine-readable, human-auditable, and export-ready.
NASA-grade systems-engineering artifact sets from a mission brief.
Drop a mission brief. Blueprint generates the complete NASA SE Handbook §6.7 artifact set (35 documents, every claim cited back to your brief) in 10–15 minutes. The pack that normally takes 80 hours of SE writing.
Break the trade-off optimization can't.
Describe an engineering problem in plain language. TIPS works the contradiction through the full TRIZ method (Contradiction Matrix, Su-Field standards, evolution trends) and returns scored, non-obvious concepts, each traced to the inventive principle that produced it.
Tools in development.
Hypothesis generation, evidence synthesis, and experimental design. The same graph-native reasoning, applied to scientific problem spaces.
Questions, partnerships, investor inquiries, or just want to talk shop
about systems engineering. We'd love to hear from you.