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Editorial Advisory Board

  • Professor Andrea M. Armani, University of Southern California
  • Ruti Ben-Shlomi, Ph.D., LightSolver
  • James Butler, Ph.D., Hamamatsu
  • Natalie Fardian-Melamed, Ph.D., Columbia University
  • Justin Sigley, Ph.D., AmeriCOM
  • Professor Birgit Stiller, Max Planck Institute for the Science of Light, and Leibniz University of Hannover
  • Professor Stephen Sweeney, University of Glasgow
  • Mohan Wang, Ph.D., University of Oxford
  • Professor Xuchen Wang, Harbin Engineering University
  • Professor Stefan Witte, Delft University of Technology

How EPWK’s AI Engine Powers Precise Matches in the Global Creative Market

By: Get News

As the global creative economy rapidly expands, many businesses and service providers still struggle to connect effectively. EPWK’s intelligent AI matching engine is bridging this gap with a data-driven infrastructure designed to match creative needs with the right talent—fast.

Two Patents Behind the Engine

To tackle challenges like vague project descriptions and inefficient talent discovery, EPWK developed a proprietary Personalized Task Recommendation Engine backed by two core patents:

• “Tri-partite Graph Matching Method”: Leverages historical data from service providers and project tags to deliver personalized recommendations while avoiding information overload.

• “Latent Factor Model with Correction Vector”: Enhances matching precision through behavioral modeling, addressing cold start issues for new users and tasks.

With these tools, the platform matches buyers and sellers with speed and accuracy. For example, a business owner in Guangzhou seeking a mini-app for aroma diffuser control was connected to the right development team within 30 minutes.

From Vague Requests to Structured Requirements

When a client requests a “Chinese retro-style logo,” EPWK’s AI Assistant kicks in. Built on DeepSeek’s NLP tech, it asks follow-up questions—like industry type or color preferences—and turns casual language into structured project briefs.

Features include AI Chat Interface: Guides clients through task clarification and standardization and smart Publishing: Auto-generates task templates, saving time and reducing errors.

A travel company in Guangxi used this system to submit an app development request, which the engine translated into specific technical points like “minimalist UI” and “membership system,” quickly connecting them to a Shenzhen-based team.

A Self-Evolving AI Engine

EPWK’s AI engine continuously improves through real-time feedback: win rates, satisfaction scores, and project outcomes all feed back into the model.

When “AI Content Creation” became a new service category in 2025, the engine trained itself on those verticals, expanding its capabilities to match large language model developers and AI writers.

Now covering over 300 service categories across design, development, video, marketing, AI, writing, and more, the platform’s growing dataset further sharpens its matching performance.

EPWK is operated by Xiamen EPWK Network Technology Co., Ltd., a national high-tech enterprise in China and a Nasdaq-listed company (EPWK) as of February 6, 2025. It has 179 tech achievements (including 137 software copyrights) and 17 patent applications (9 granted). The company is recognized as a leader in digital crowdsourcing infrastructure and a key player in China’s creative economy.

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