Haizol Recognised for AI Driven Custom Parts Manufacturing at National Industrial Internet Competition
How Haizol uses AI to make online custom parts manufacturing more transparent predictable and scalable through verified suppliers structured RFQs and factory direct sourcing.
Table of Contents
The 7th National Finals of the Industrial Internet Competition were held in Beijing from December 10 to 12, 2025. During the event, Haizol was awarded Second Prize at the national level, ranking second overall in the leading enterprise group, for the real-world application of its AI-driven manufacturing platform.
After multiple evaluation rounds, 241 projects advanced to the industry finals, with 63 projects selected for the national stage. Among them, 43 enterprises competed in the leading group, including central and provincial state-owned enterprises and research institutes across power generation, oil and gas, metallurgy, non-ferrous metals, shipbuilding, and aviation.
This result represents authoritative recognition of Haizol’s platform in terms of technical maturity, deployment readiness, and measurable manufacturing impact. This announcement highlights Haizol’s recognition at a national-level industrial technology competition.
Haizol is a factory-direct online custom manufacturing marketplace that connects buyers with multiple verified Asian factories through a single RFQ, enabling them to receive and compare quotations for CNC machining, injection molding, and other non-standard parts.
The platform is built specifically for non-standard manufacturing, including CNC machining, injection molding, casting, stamping, and sheet metal fabrication, where supplier selection, quotation accuracy, and delivery coordination are traditionally difficult to manage at scale.
During the final technical defence, Liu Haitao, Vice President of Haizol, presented how the platform operates at an engineering and supply-chain level.
Haizol is built on two proprietary industrial databases:
By applying AI across these two datasets, Haizol converts manual and experience-driven sourcing decisions into repeatable, data-driven workflows. This directly addresses common failure points in online manufacturing sourcing, including supplier mismatch, inaccurate quotations, and high coordination cost across multiple factories.
Haizol’s platform operates through five integrated AI systems:
Matches RFQs to factories based on technical capability, not category labels, enabling accurate supplier selection within seconds.
Uses similarity analysis on uploaded drawings to identify factories with proven experience producing comparable parts.
Factories can generate structured quotations by combining equipment parameters, material libraries, process modules, and indirect cost models.
Enables R&D teams, procurement, and factories to align on technical details early, reducing revisions and sampling delays.
Coordinates multi-factory and multi-process production paths to improve delivery certainty for complex orders. Together, these systems replace fragmented communication with standardised, auditable manufacturing workflows.
Haizol will continue to invest in data and AI to strengthen transparent, factory-direct manufacturing collaboration across global supply chains. The goal remains consistent: faster response, more stable delivery, and lower sourcing risk for custom manufacturing projects.
Founded in 2015, Haizol operates a global marketplace for custom parts manufacturing and industrial supply chain collaboration.
The platform connects supply-demand matching, quotation, production coordination, quality control, and settlement into a single digital workflow. By combining engineering knowledge with structured data and AI, Haizol supports flexible, on-demand manufacturing for international buyers sourcing from Asia.
Haizol focuses on one outcome: making global manufacturing sourcing more transparent, predictable, and scalable.
Join Haizol for free - Asia’s leading custom manufacturing marketplace. Connect with over 700,000 suppliers and get multiple quotes with one request.
Latest Content