NETCLASS TECHNOLOGY INC Receives Outstanding Case Award for Its Multi-Agent AI Language Teaching System at 2026 Digital Lifelong Learning Conference

NetClass Technology (Nasdaq: NTCL) received an Outstanding Case Award for its multi-agent foreign language teaching system at the 2026 Digital Lifelong Learning International Conference.

Rhea-AI Summary

NetClass Technology (Nasdaq: NTCL) received an Outstanding Case Award for its multi-agent foreign language teaching system at the 2026 Digital Lifelong Learning International Conference.

The conference took place October 16–17 at Shanghai Open University, co-organized with UNESCO UIL and UNESCO IITE. The recognized case combines the company's AI English Go instruction platform and CEPA assessment engine, using specialized AI agents and teacher review for language assessment and personalized learning support. The system has scaled to nearly 100 institutions, supporting over 40,000 students and three accredited Shanghai university courses.

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$0.54 – $0.60 Day Range

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On Oct 30, the day this news came out, the latest delayed price for NTCL is 2.00% above the previous close. Argus tracked a trough of -16.9% from its starting point during tracking. Our momentum scanner has recorded 9 alerts for this stock so far that day. The latest delayed price is $0.55. Relative volume is above average at 2.0x the average.

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Key Figures

Institutional reach: Nearly 100 institutions Students supported: Over 40,000 students Accredited courses: Three courses

Institutional reach

Nearly 100 institutions

AI language teaching system

Students supported

Over 40,000 students

AI language teaching system

Accredited courses

Three courses

Shanghai university courses

Previous AI Reports

1 past event · Latest: May 23

Same Type 1 event

1. May 23

   AI system deployment

   24h Move

   -21.4%

   Deployed system covered 71 colleges across 20 provinces and served over 20,000 teachers and students.

24h Move is the share-price change in the day after each event; other market factors may also have contributed.

Key Terms

multi-agent architectures, large language models, human-in-the-loop controls

3 terms

multi-agent architectures technical

"applies multi-agent architectures and large language models (LLMs)"

A multi-agent architecture is a software design in which a system’s behavior emerges from multiple autonomous ‘agents’—independent programs or processes—that interact, coordinate, or compete to perform tasks. Each agent has its own goals, capabilities, and information, and agents communicate through defined protocols (messages, shared environments, or marketplaces); the overall system can be centralized (a coordinator directs agents) or decentralized (agents negotiate or respond to local signals). This architecture is used to split complex problems into specialized roles, enable parallelism and fault tolerance, and produce coordinated outcomes through interaction rules, though it also introduces design complexity around agent communication, consistency, and conflict resolution.

large language models technical

"applies multi-agent architectures and large language models (LLMs)"

Large language models are advanced AI systems trained on vast amounts of text to understand and generate human-like writing, like a very fast reader and writer that learns patterns in words and sentences. They matter to investors because they can change how companies operate—automating customer service, speeding analysis, cutting costs, creating new products—and they introduce risks around accuracy, security and regulation that can affect a firm’s revenue and reputation.

human-in-the-loop controls technical

"specialized software agents with human-in-the-loop controls"

Controls built into automated systems that require a person to review, authorize, or modify a machine-made decision or action before that decision is finalized or executed. They typically operate as checkpoints in workflows—examples include manual approvals of trades flagged by an algorithm, human review of exception reports produced by transaction monitoring, or a compliance officer signing off on automated filings—and are designed to combine automated efficiency with human judgement; they do not remove the need to design, monitor and test the underlying automation and can introduce delays or single‑point dependencies if poorly implemented.

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• Project Recognized by UNESCO IITE, UIL, and Shanghai Open University for AI-Driven Education Innovation
• Proprietary AI English Go and CEPA Platforms Combine Multi-Agent Architecture with Automated Diagnostics and Teacher Review
• System Scaled to Nearly 100 Institutions, Supporting Over 40,000 Students and Three Accredited Shanghai University Courses
  
  

SINGAPORE and HONG KONG, Oct. 30, 2026 (GLOBE NEWSWIRE) -- NETCLASS TECHNOLOGY INC (Nasdaq: NTCL; the “Company” or “NetClass”), a B2B smart education IT solutions provider with offices in Shanghai, Hong Kong, Singapore and Tokyo, today announced that its case study on multi-agent foreign language education received the Outstanding Case Award at the 2026 Digital Lifelong Learning International Conference.

The conference was held on October 16-17, 2026, at Shanghai Open University, co-organized by Shanghai Open University, the UNESCO Institute for Lifelong Learning (UIL), and the UNESCO Institute for Information Technologies in Education (UNESCO IITE). NetClass’s case, titled “Multi-Agent Collaboration-Driven Foreign Language Teaching Assessment and Personalized Learning Support Practice,” was selected from a nationwide pool of submissions on AI-empowered smart learning ecosystems.

The recognized initiative applies multi-agent architectures and large language models (LLMs) to common constraints in conventional foreign language instruction, such as limited oral practice, delayed grading feedback, and the difficulty of converting evaluation metrics into tailored lesson plans. Built on the Company’s proprietary AI English Go instruction system and CEPA assessment engine, the platform coordinates specialized agents to analyze discrete language components, including pronunciation, vocabulary, grammar, discourse structure, and pragmatic usage. To address common LLM output variance and explainability issues, the software incorporates confidence score fusion, anomaly flagging, dynamic routing, and human instructor review for open-ended assignments like oral dialogue and composition.

At the conference, NetClass Deputy General Manager, Jing Wang, presented the case study and participated in discussions with academic researchers and industry peers on practical integration methods for AI in higher education.

“Receiving this recognition from prestigious institutions like UNESCO IITE and UIL validates our conviction that multi-agent AI architectures represent the future of educational technology,” said Dr. Jianbiao Dai, Chairman and Chief Executive Officer of NetClass. “Language teachers frequently spend excessive hours on routine error correction rather than direct instruction. By assigning discrete evaluation tasks to specialized software agents with human-in-the-loop controls, our platform provides reliable, diagnostic feedback that faculty can use in real time. This award fuels our strategic ambition to continuously push the boundaries of applied AI, expanding our multi-agent framework across broader subjects, diverse languages, and new global markets to fundamentally redefine digital education.”

About NETCLASS TECHNOLOGY INC
NETCLASS TECHNOLOGY INC is a B2B smart education specialist with offices in Shanghai, Hong Kong, Singapore, and Tokyo, providing innovative IT solutions to schools, training institutions, corporations, public agencies, and other organizations. The Company’s services include SaaS subscription services and application software development, and, through its joint venture, interactive AI companion smart hardware, with solutions spanning teaching and campus management, online teaching, examinations, epidemic prevention, data storage, EDC (Education Credit) blockchain systems, and lecturer evaluation services. The Company’s mission is to deliver reliable, high-quality products that drive sustainable growth for our customers. For more information, please visit the Company’s website: https://ir.netclasstech.com

Forward-Looking Statements
All statements other than statements of historical fact in this announcement are forward-looking statements. These forward-looking statements involve known and unknown risks and uncertainties and are based on the Company’s current expectations and projections about future events that the Company believes may affect its financial condition, results of operations, business strategy and financial needs. Investors can identify these forward-looking statements by words or phrases such as “approximates,” “believes,” “hopes,” “expects,” “anticipates,” “estimates,” “projects,” “intends,” “plans,” “will,” “would,” “should,” “could,” “may” or other similar expressions. The Company undertakes no obligation to update or revise publicly any forward-looking statements to reflect subsequent occurring events or circumstances, or changes in its expectations, except as may be required by law. Although the Company believes that the expectations expressed in these forward-looking statements are reasonable, it cannot assure you that such expectations will turn out to be correct, and the Company cautions investors that actual results may differ materially from the anticipated results and encourages investors to review other factors that may affect its future results in the Company’s most recent Annual Report on Form 20-F and other filings with the U.S. Securities and Exchange Commission.

For investor and media inquiries, please contact:
NETCLASS TECHNOLOGY INC
Investor Relations
Email: ir@netclasstech.com

Jackson Lin
LLYC
Email: jian.lin@llyc.global