美光速造 launches three AI large-model software products for metal 3D printing, marking a shift to AI-driven additive manufacturing.
Originally reported by 南极熊
美光速造 (Bright Laser Technologies, BLT), a Chinese metal additive manufacturing OEM, held an online conference on June 26, 2026, unveiling three AI-driven software products covering the full metal 3D printing workflow. The releases include FastLayer 7, an AI-powered pre-processing and slicing platform; AM Build, a dynamic process-adaptive model for real-time parameter adjustment during printing; and AM Mind, a large-language model for autonomous equipment operation and maintenance. BLT claims its installed base exceeds 3,000 metal printers across 80 countries, and its R&D team of over 60 master’s and doctoral-level staff has been developing proprietary software for a decade.
This launch signals a strategic pivot from hardware-centric competition-where Chinese OEMs have already driven multi-laser, large-format LPBF machines to market-toward software and AI as the next differentiation axis. BLT’s AM Build model targets persistent pain points in metal AM: unsupported overhangs, thin-wall distortion, and surface quality variability, which have historically required manual parameter tuning and extensive post-processing. By embedding process knowledge into an adaptive model, BLT aims to reduce operator skill dependency and improve first-pass success rates, directly addressing the qualification and repeatability barriers that limit metal AM adoption in aerospace and medical production. The move also reflects a broader industry trend where Chinese AM firms, having matched Western hardware specs, are now investing in software ecosystems to capture higher-value service and recurring revenue.
For BLT, the practical challenge is proving that these AI models deliver consistent, measurable improvements across diverse part geometries and materials, not just in controlled demos. The company must also demonstrate that AM Mind’s maintenance model can reduce machine downtime in real production environments, a key metric for service bureaus and serial manufacturers. If BLT can validate these tools with customer data and integrate them into existing MES workflows, it could strengthen its position in export markets where software maturity is increasingly a purchasing criterion. For now, the announcement is a credible step toward software-led differentiation, but execution and customer evidence will determine whether it moves beyond marketing into operational reality.
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