BlueOcean AI connects manufacturing quotes, scheduling and inspection with LevelField-2
The AMW Read
The integrated workbench and updated machining model extend factory operations AI, but reported demonstrations and cumulative customer counts do not establish broader production impact.
BlueOcean AI connects manufacturing quotes, scheduling and inspection with LevelField-2
BlueOcean AI, an industrial AI company incubated by Shanghai Jingzhi Group, demonstrated its order-fulfillment workbench at the 2026 China International Industry Fair in Shanghai. The platform combines process-planning, production-scheduling and visual-inspection agents around a shared manufacturing drawing, connecting quotations, process cards, delivery estimates and shop-floor reporting. The company also released LevelField-2, a 9-billion-parameter machining model built on an open Qwen base, under the Apache 2.0 license. It says training across both model generations used more than 100,000 drawing sets, with annotation and validation involving 36 experienced process specialists.
The launch belongs to enterprise operations AI: its commercial proposition is coordinating factory work from order intake through delivery. LevelField-2 generates process cards using a factory's equipment, tools, inventory and machining practices, with process-engineer review required before production. Open distribution makes the model commercially accessible, while the workbench competes on integration with existing factory systems and adaptation to operating conditions. The source reports demonstrations and internal factory use, but provides no quantified improvement in delivery reliability, quoting accuracy or production costs.
For builders and investors, the concrete diligence question is whether shared drawing data reduces costly handoff errors across quoting, planning and inspection. BlueOcean AI says its functions were first tested on real orders at Shanghai Jingzhi's Kangqiao factory and that it has served 500 customers cumulatively; that figure does not establish adoption of the newly demonstrated workbench. Evaluation should focus on engineer correction rates and delivery performance across factories with different equipment.