From legacy iteration to AI-first generative design

The past: start from known templates and nudge. The future: generate novel architectures with constraints baked in.

Problem — the bottlenecks

  • Manual iteration over decades-old starting forms
  • Limited exploration under time/budget constraints
  • Late discovery of tolerance / manufacturability issues

Solution — human–AI teaming

  • Diffusion/transformer search over design spaces
  • Expert curation + constraint-aware objectives
  • Tolerance and supplier constraints in-loop

Workflow at a glance

  1. Define mission & constraints (SWaP, MTF, Strehl, envelope)
  2. AI proposes families of feasible designs
  3. Engineer selects candidates; refine with physics/tolerances
  4. Converge to manufacturable design; lock vendor options