AI-driven programming has moved from proof-of-concept to production reality – and CloudNC’s latest release, CAM Assist 2.0, marks another milestone in that evolution. The update brings greater control, transparency, and flexibility to the machining floor, giving programmers a deeper understanding of how AI makes its decisions.
We sat down with Theo from CloudNC to discuss what’s new in CAM Assist 2.0, how it’s changing the CAM landscape, and what the next few years hold for AI in manufacturing.
Interview
MTN: “CAM Assist 2.0 has just launched. What’s the biggest difference customers will notice, and how will it develop over the next year or two?”
Theo: “Two things: control and clarity. CAM Assist 2.0 keeps the speed our users love, but it now breaks the AI into clear steps with richer feedback before anything is committed back to your CAM Package. You can configure machines, materials and tools, assess the part, and review each generated strategy – so you stay firmly in the loop.”
“Looking ahead, you’ll see that human-in-the-loop concept go even further: our forthcoming strategy editor lets programmers understand and steer the AI’s reasoning as it generates operations.”
MTN: “Moving beyond 3-axis. When can shops expect AI programming for full 5-axis, turning and mill-turn – and what’s holding that back?”
Theo: “Today we reliably accelerate 3-axis and 3+2. Full simultaneous 5-axis and complex turn/mill will come in stages: first constrained patterns and families of parts, then broader coverage as the models and verification mature. Realistically, think of initial measured rollouts over the next 24 months rather than a single big bang.”
“What’s hard? The problem we’re solving is incredibly difficult. There are an infinite number of ways of machining any part of any component, which means the computational challenge is immeasurable. Then, you add in that this is a physically complicated environment where any mistake potentially damages very expensive equipment, and the end product has to be perfect. Getting an AI to cope with those factors is a next-level challenge.”
MTN: “Working across different CAM systems. Do you see a future where CAM Assist works seamlessly across all major platforms?”
Theo: “Yes – that’s the point. We already integrate with Autodesk Fusion, Mastercam and Siemens NX and we’ll keep expanding onto new platforms. Our goal is a consistent ‘strategy layer’ on top of each CAM’s APIs, so your shop gets the same quality of decision-making wherever your programmers prefer to work.”
MTN: “Trust and risk. If an AI-generated toolpath doesn’t perform as expected, how should responsibility be shared?”
Theo: “AI shouldn’t be a black box that asks you to take the risk. Our view is shared responsibility with clear guardrails: we provide conservative defaults, staged reviews, and transparent reasoning; you keep ultimate control to simulate, tweak and approve. CAM Assist never presses Cycle Start – it accelerates your decision-making and pushes strategies back into your CAM where you verify per your shop standards.”
MTN: “The bigger workflow picture. How far away are we from connecting quoting, fixture design, CAM and scheduling in one joined-up AI process?”
Theo: “Parts of that are already here. CAM Assist can check machinability and produce accurate cycle-time estimates in just a few clicks – that feeds quoting. Our goal is to keep adding tools and developments that increase the utility of our software even further, making machinists 10x more productive.”
MTN: “The skills question. With programmer shortages, how will the CAM programmer’s role change?”
Theo: “Not as much as you might think. There is a skills crisis in this industry – there aren’t enough people to do the work – so we need to solve that with technology. What CAM Assist does is accelerate the boring, tedious parts of the job, allowing the CAM programmer to use their talents where they make most difference – accelerating cycle times and solving problems. Shops that lean in will upskill faster and make their experts force multipliers for the whole team.”
MTN: “Hard results. What ROI are customers seeing right now?”
Theo: “Across shops we see 60–80% reductions in programming time, and dramatic throughput gains – customers talk about going from hours to minutes on typical jobs.”
“Aerospace supplier MSP, for example, reports CAM Assist gets them 80% of the way in 7 minutes, with a programmer spending 15 minutes to finish – work that previously took 1.5–2 hours. Others report overall productivity lifts approaching ~90% in their CNC departments once you compound faster programming, more jobs started, and better standardisation.”
“At a market level, adoption has scaled to hundreds of US customers, reflecting the ROI story we hear daily.”
MTN: “Industry trends. What will shape CNC over the next five years – and how is CloudNC positioned?”
Theo: “AI-first CAM becomes standard for 3-axis/3+2; 5-axis and turn/mill follow in well-defined stages, with human-in-the-loop tooling.”
“Labour constraints persist, so the winners will be the shops that use AI to amplify scarce expertise rather than replace it.”
“CloudNC’s role is to industrialise AI for CAM: fast where it should be, transparent where it must be, and integrated wherever you work. That’s what CAM Assist 2.0 delivers today, and what our roadmap extends over the next few years.”
Final Thoughts
From its early promise of faster programming to today’s transparent, collaborative AI workflows, CloudNC’s CAM Assist 2.0 marks a turning point in how machine shops approach digital manufacturing. With deep integration across CAM systems, measurable ROI, and a roadmap that embraces both human expertise and machine intelligence, it’s clear CloudNC isn’t just building software – it’s defining what AI in CAM will look like for the decade ahead.
For further information, visit cloudnc.com.
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