Guangdian Yuntong Wangdao Large Model

What is the Wangdao large model developed by Guangdian Yuntong?

The Wangdao large model developed by Guangdian Yuntong is a large-scale industry model of billions of parameters, created independently by Guangdian Yuntong Group Co., Ltd.; it is designed to serve industries such as fintech, government services, and urban intelligence.

It is built on the aiCore System digital platform and consists of industry-specific models, a knowledge hub, agent applications, enterprise interfaces, as well as integrated hardware and software solutions; it is not a simple public chatbot.

Product positioning and current status

• Wangdao was released in 2023, and subsequently gave rise to various products such as a large-model application platform, Copilot, a knowledge platform, and integrated systems.
• By June 2025, the registration for generative artificial intelligence services will be completed, with the aim of advancing their commercial use in key sectors such as finance and government services.
• The currently publicly available page is still accessible, but the protected features require logging in through the enterprise collaboration platform; individual self-registration is not available.
• The term “lawllm” in the product’s address should not be interpreted as referring to tasks related solely to law; in reality, it covers areas such as finance, government affairs, auditing, state assets management, policing, office operations, maintenance, and urban governance.

Four types of core competencies

Scene text analysis

• Perform summarization, error correction, information extraction, text classification, and topic word generation on systems, reports, work orders, and general documents.
• It is suitable for extracting key points, tags, and structured fields from large volumes of unstructured data.
• The extraction rules, document length, supported formats, and batch processing limits must be confirmed according to the deployment version.

Domain knowledge Q&A

• Leveraging the enterprise knowledge base to handle product inquiries, system lookups, intent recognition, and knowledge retrieval.
• It supports context understanding and multi-turn conversations, and enables the conversion of internal policies or business knowledge into question-and-answer formats intended for employees and customers.
• Whether the answer includes evidence, the scope of the recall, and permission controls depend on the knowledge base and application configuration.

Government and enterprise data analysis

• It supports tasks such as code writing and execution, entity extraction, relationship extraction, report generation, and trend prediction.
• Natural language to SQL conversion allows non-technical users to query structured data using business questions, and it also helps in analyzing or optimizing SQL queries.
• The production database must have read-only permissions, defined query ranges, audit logs, and result verification; it is not possible to execute unreviewed code directly.

Creative text generation

• It can generate texts such as copy, summaries, titles, topics, stories, and character profiles.
• Companies can integrate these capabilities into documents, reports, customer service tools, and office assistants, thereby reducing the need to draft content repeatedly.
• The generated draft may still contain factual inaccuracies, formatting errors, or inappropriate wording, and it requires review by business staff.

Over 60 types of industry skills

More than 60 items provide an overview of the overall product capabilities; the specific skills available, industry-related data, and scope of delivery may vary depending on the project version.

Vertical industry scenarios

Wisdom Knowledge Platform and Agent Orchestration

• The knowledge platform enables enterprises to create custom knowledge bases, transforming various business materials into searchable and queryable knowledge assets.
• It is possible to dynamically load dozens of models, and select Wangdao, DeepSeek, or other available models depending on the task at hand.
• Low-code visual orchestration connects models, knowledge bases, tools, and business processes into agents.
• Once the application is developed, it can be deployed in the enterprise’s business system and operated in conjunction with high-concurrency inference services.
• The aiCore Knowledge Platform 2.0, to be launched in 2026, will further enhance the knowledge center, agent center, permission control, and credible tracking capabilities.

Wangdao DeepSeek large-model all-in-one system

• The all-in-one device comes pre-installed with an optimized model runtime environment that supports DeepSeek V3, R1, and their distilled versions.
• The product includes full-stack AI tools and a visual interface, allowing for the creation of knowledge bases locally as well as the organization of custom agents.
• It is compatible with domestic computing platforms, and is suitable for government and enterprise projects that require high levels of control over data transfer, deployment timelines, and operational management.
• Equipment maintenance, legal risk management, and document writing have been implemented; however, the hardware model, video memory, concurrency capacity, and response speed need to be confirmed based on the configuration.
• The integration of DeepSeek does not mean that the Wangdao model, the platform code, or the all-in-one solutions become open-source products.

Deployment and usage process

1. Identify the objectives and tasks, user roles, data sensitivity levels, accuracy metrics, and the manual approval steps that must be retained.
2. Choose MaaS, an application platform, a private knowledge platform, or an integrated hardware and software solution, and ensure that domestic computing power and network infrastructure are available.
3. Clean up systems, documents, databases, and historical tickets; establish knowledge classification, access permissions, responsibilities for updates, and rules for deletion.
4. Select models, knowledge bases, and tools within the knowledge platform to use visual workflow orchestration for creating agents that can handle tasks such as querying, extraction, analysis, or reporting.
5. Use a real but anonymized test set to evaluate recall, factual accuracy, permission isolation, refusal to respond, and high-risk outputs.
6. After integrating with existing business systems, it is rolled out in phases, with continuous monitoring of logs, costs, the rate of manual corrections, and the timeliness of available knowledge.

Comparison of product forms

Suitable for users

• Customer service, operations, risk management, and data teams in banks, insurance companies, and other financial institutions.
• Teams responsible for the development of knowledge services and business systems in government agencies, state-owned enterprise units, police departments, and urban governance organizations.
• Scenarios for regulatory search, anomaly analysis, and report generation in the audit department.
• A corporate group that possesses a large number of internal documents, databases, and device logs.
• System integration projects that require domestic computing power for adaptation, private deployment, and agent orchestration.

Advantages and capabilities boundaries

Main advantages

• Industry models, knowledge governance, agent development, and computing power delivery together form a complete product portfolio suitable for complex government and enterprise projects.
• It focuses on finance, government services, auditing, and urban intelligence, offering industry-specific skills that can be combined directly.
• It supports domestic technologies such as Ascend and MindSpore, as well as local integrated machine deployment.
• It is possible to use self-developed industry models, as well as to integrate models such as DeepSeek through the knowledge platform for collaborative use.

Usage restrictions

• It is not possible to register for a trial directly through the public website, and individual users cannot use it as a regular free chatting service.
• There are no unified publicly specified standards for model versions, context, file format, concurrency, latency, and API quotas.
• In industry Q&A, risk warnings, and trend forecasts, illusions, omissions, or outdated conclusions may still occur; therefore, manual review is necessary.
• Low-code orchestration can reduce development efforts, but data governance, permission design, evaluation, and system integration still require a specialized team.
• \"Independent innovation,\" \"safety and reliability,\" and technical certifications do not guarantee that all deployments will meet customers’ security and compliance requirements.

Prices and Purchases

The individual free quota, standard subscription fee, unit price for pay-as-you-go usage, or unified price of the all-in-one system have not been made public; therefore, it cannot be considered a \"free premium\" offering.

When making purchases, it is necessary to separate the costs related to model licensing, computing resources, implementation and integration, data governance, operation and maintenance, upgrades, training, and future capacity expansion.

API and open-source status

• The Wisdom Knowledge Platform enables enterprises to call the relevant interfaces as needed, but public developer documentation, authentication methods, rate limits, and standard pricing have not yet been released.
• No official SDKs, plugins, example projects available for the public, nor any verifiable GitHub repositories have been found yet.
• The model weights, training code, and platform code do not come with an open license; therefore, Wangdao should be regarded as a closed-source commercial product.
• The open-source or ecosystem nature of DeepSeek, Ascend, and MindSpore cannot be applied to the open-source licensing of Wangdao’s products.
• Interface fields, model versions, data destination, error handling, and service levels should be specified in the enterprise project documentation and contracts.

Privacy, security, and contractual considerations

• The product highlights private deployment, data retention within the domain, fine-grained permissions, and reliable traceability; however, the actual performance depends on the configuration choices made during procurement and the quality of implementation.
• The public page does not yet provide a separate and complete user agreement, privacy policy, information on data retention periods, rules for using the training data, or terms regarding copyright of the outputs.
• The contract should specify whether the input data is used for training, log retention and deletion, administrator access, backups, disaster recovery, and notification of security incidents.
• For police, audit, financial, and government data, minimum permissions, data masking, classification, operation auditing, and manual approval should be implemented.
• It is also necessary to agree on the ownership of the models and knowledge bases, the rights to the content generated, licenses for third-party models, service levels, acceptance criteria, as well as procedures for refunds and withdrawal from the migration process.
• Before going live, the organization’s test set should be used to verify issues such as unauthorized data retrieval, prompt injection, leakage of sensitive information, incorrect references, and the generation of high-risk decisions.

Frequently Asked Questions

Can one register for the Wangdao large model for free as an individual?

The current public page does not offer self-registration for individuals; protected functions require logging in through a corporate collaboration platform, and the free quota available for individuals is also not disclosed.

Is the Wangdao large model suitable only for legal applications?

No, it covers scenarios such as finance, government affairs, auditing, state-owned assets, policing, office operations, maintenance, corporate data analysis, and urban governance.

Does Wangdao support private deployment?

Local delivery is supported through the knowledge platform and large-model integrated systems; the specific models, computing power, concurrency levels, and security settings must be determined based on the requirements of each project.

Does Wangdao support DeepSeek?

The Enlightenment Knowledge Platform integrates DeepSeek V3 and R1, and the all-in-one system also supports these models as well as their distilled versions.

Does Wangdao have a public API?

The enterprise knowledge platform supports project interfaces, but it does not yet provide documentation for public developers, options for requesting access keys, or standard pay-as-you-go pricing.

Is the Wangdao large model an open-source product?

It is not an open-source product that has been officially recognized; the model weights, platform code, official repository, or open license are not yet available publicly.

Summary

The Wangdao large model developed by Guangdian Yuntong is more suitable for government and enterprise clients who require industry-specific knowledge, agent-based applications, domestic computing power, and private deployment options.

When conducting an evaluation, the performance of the model, knowledge governance, interface integration, hardware configuration, security measures, and long-term maintenance should all be taken into account as part of the procurement process, rather than focusing only on the public chat interfaces.