Zephyra provides specialist AI agents for manufacturing that balance quality, costs, and emissions across concept design, tooling design, and production optimization. The platform evaluates millions of geometry-material-process configurations to deliver feasibility verdicts, optimized cooling layouts, and validated process parameters in minutes rather than weeks. Customers report analysis time reductions from 48 hours to 4 hours and energy savings of 20-50% on existing presses.
Funding
Funding not disclosed
Founders
Product
Problem
Manufacturing companies face slow, expensive design-for-manufacturability (DFM) reviews and mold design cycles that typically take 2-8 weeks and cost thousands of euros. Manual process tuning relies on trial and error, leading to tooling write-offs, energy waste, and missed quote opportunities when responding to RFQs.
Solution
Zephyra deploys a team of physics-trained AI agents that evaluate manufacturing feasibility, material selection, process technology, and economics across millions of configurations in minutes. The platform covers the full manufacturing lifecycle: concept design catches manufacturability issues before commitment, tooling design optimizes cooling layouts and gate positions before steel is cut, and production optimization tunes process parameters on existing presses. Each design iteration tracks quality, cost, cycle time, and CO₂ emissions, with results validated for export to Moldflow, Ansys, and Abaqus. The system delivers ranked shortlists, risk flags, and KPI dashboards that enable engineers to make data-driven decisions without weeks of simulation work.
Target Audience
Primary users are toolshops responding to RFQs, OEM and tier-1 design engineers catching design issues before production, and suppliers who need sustainability data for customers requesting carbon reporting.
Features
- Physics-trained AI agents that evaluate geometry × material × process × economics combinations, exploring up to 2.34 million configurations per part
- Concept design module providing feasibility verdicts, ranked material shortlists, process recommendations (injection molding, die casting, thermoforming, additive manufacturing), and cost estimates
- Tooling design optimization for cooling layouts and gate positions, reducing cycle times from 90s to 30s and temperature differentials from 17°C to 9°C
- Production optimization that cuts energy consumption by 20-50% on existing presses with CBAM-ready CO₂ reporting
- Automated risk flagging for manufacturability issues such as wall thickness, draft angles, and filling pressure problems
- Handoff-ready exports to Moldflow, Ansys, and Abaqus for downstream validation
- KPI dashboard tracking energy per piece, CO₂ per piece, and cycle time improvements with baseline comparisons