Simulate

the impact of parameter changes

on your process and master your production performance

Most AI vendors analyze your data remotely and deliver generic recommendations. Juno starts with plant visits — our engineers walk your production line, map the process with your team, and capture the expertise that drives quality. We then build custom AI models that combine your data with this domain knowledge. It's not plug-and-play AI; it's AI built specifically for your process.

Juno specializes in continuous and batch manufacturing processes including injection molding, extrusion, blow molding, coating, mixing, and assembly. If your process has adjustable parameters (temperature, pressure, speed, time) and measurable quality outcomes, Juno can optimize it.

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Our standard pilot runs 6 weeks: 1 week for discovery and process mapping, 2 weeks to build and validate your custom AI model, then 2-3 weeks of live production trials to prove results. You'll see recommendations applied on your actual production line during the pilot — not just theoretical analysis.

No. Juno is designed for process engineers, not data scientists. We handle all the AI complexity — data cleaning, model training, and validation. Your team focuses on what they do best: understanding the process and deciding which recommendations to implement.

That's normal. Most plants have data gaps, inconsistent timestamps, or missing quality records. Part of our discovery phase is auditing your data and identifying what's usable. We've built pilots with as little as 3 months of historical data when combined with strong process expertise from your engineers.

All data and process knowledge captured during discovery and pilots remain strictly confidential. We sign NDAs upfront, store data in secure, isolated environments, and never share insights across customers. Your competitive process expertise stays yours — Juno just helps you leverage it more effectively.

Results vary by process and KPI focus, but pilot customers typically see 15-30% improvements in their target metric — whether that's reduced scrap, improved first-time yield, faster cycle times, or lower energy consumption. We define success criteria upfront during kickoff so expectations are clear from day one.