Company Introduction (Wuhan Ding’an Huasheng Technology Co., Ltd. · TUEO)
Brand: site-wide unified TUEO (legal company name: Wuhan Ding’an Huasheng Technology Co., Ltd.) Purpose: content for the “About us” page of the official website · external business introduction
One-line positioning
Wuhan Ding’an Huasheng Technology Co., Ltd. is a provider of the intelligent foundation for enterprise digitalization in the AI era — with the fully self-developed TUEO platform, it helps enterprises define systems by task, reuse and AI-enable their existing capabilities, and run continuously on a private, self-operated foundation. AI participates in the organization as full-time employees, operating the business alongside people within the customer’s own environment.
Company profile
Wuhan Ding’an Huasheng Technology Co., Ltd. (hereafter “Ding’an Huasheng”) is a technology company focused on the research and application of enterprise-grade AI collaboration platforms, committed to fully self-developed core technology. Starting from the complete chain of AI employees entering the organization — identity, knowledge-memory, compute, collaboration, orchestration, capability, execution, coding, operations, plugins — it has self-developed ten products: identity, engram, inference, cohort, studio, capabilities, executor, codex-build, skillplugins, console, forming a complete platform system centered on the TUEO intelligent foundation: letting AI enter organizational operations as full-time employees, letting an enterprise’s existing systems be AI-enabled and reused, and running continuously on a self-operated foundation.
TUEO’s core thesis: in the era of AI programming, what enterprise digitalization truly lacks is not more systems, but an intelligent foundation that links the “definition, production, operations, updates, and coordination” of systems into one complete loop. Data silos are a “reading” problem and are largely solved; system silos are a “doing” problem — AI needs to log into systems, know what capabilities they have, execute actions safely, and leave an audit trail for every action. TUEO does not replace an enterprise’s OA / ERP / CRM / MES; instead, for the first time, they become capabilities that AI can invoke, authorize, audit, and meter.
Around core areas such as agent collaboration, high-concurrency scheduling, and data security, the company has filed multiple invention patents and software copyrights, building a solid technology moat.
What we do: the intelligent foundation for enterprise digitalization
TUEO is a system of ten products covering the three layers of the intelligent foundation:
- Definition layer — define systems by task (not develop systems): business raises requirements, AI analyzes them into tasks, the AI team takes them on, reuses existing capabilities, tests, and delivers. Carried by the cohort work-order pipeline + studio application orchestration + executor execution base;
- Coordination layer — AI-enable capabilities, govern system silos: register an enterprise’s existing systems as capabilities, authorize them, host their credentials, and let them be safely invoked by AI. Carried by the capabilities platform + skillplugins plugin SDK + identity foundation;
- Operations layer — unified operations base: new systems, old systems, AI systems — one entry point to operate the whole stack. Carried by the console operations platform + executor.
- Three foundation bases — cross-cutting support for everything above: identity governs “who you are and what you can do,” engram governs “what it knows and remembers,” inference governs “how compute and models are served.” The three bases of identity, knowledge, and compute are consumed by every product in the suite.
The ten products
| Product | In one sentence |
|---|---|
| identity | Identity foundation: one account to access every product, one directory managing people and AI employees |
| engram | Knowledge-memory base: knowledge base + conversational memory + entity graph, automatically organized and self-growing |
| inference | Compute and model serving: dual-pool compute independently managed, model serving, training, quotas and audit |
| cohort | Collaboration core: humans and AI employees work and grow together in the same workspace |
| studio | Application orchestration: business people use conversation to compose processes into thinking applications |
| capabilities | Capability coordination: the App Store for enterprise AI capabilities |
| executor | Execution base: the hands of AI, doing real work in isolated sandboxes |
| codex-build | Coding engine: AI employees really modify code and really produce MRs |
| skillplugins | Plugin SDK: one capability contract, two consumers |
| console | Operations base: turns bare metal into a production environment with one click, operates everything from one interface |
The complete software development loop
Business raises requirements → AI analyzes them into tasks → the AI team develops → testing · UAT → put into production → continuous monitoring and operations → first take stock of existing capabilities, reuse instead of redeveloping → capability coordination → back to requirements. People are AI employees, and code is replaced by tasks — systems are “defined,” run, and operated, rather than “developed” line by line.
Product philosophy
- AI is a colleague, not a tool: AI has independent judgment and a sense of proportion; it decides whether to respond or to act proactively, rather than passively executing instructions;
- Positions determine boundaries, and AI employees are equally governed: a secretary is a secretary — Su Wan is a secretary; she cannot operate operations servers. An AI’s capability boundary is jointly determined by position, responsibilities, and granted tool permissions; out-of-bounds actions are hard-rejected at the server with an audit record, following the same governance logic as human employees;
- Private deployment is the main path, not an option: full offline / air-gapped deployment is supported, data never leaves the enterprise, and everything is auditable and rollback-capable;
- Evidence-driven, never fabricated: when data cannot be obtained, show ”—”; every judgment has a source, every piece of knowledge has a sensitivity rating;
- The stronger the AI, the tighter the boundaries: zero cross-tenant access, mandatory approval for high-risk actions, sell the system rather than standalone products.
Proven in practice
- Suzhou Public Security benchmark: built a 2000+ agent collaboration platform, cutting major-case investigation turnaround time by 70% and reaching an 85% automation rate for police reports, featured in key promotion by the Ministry of Public Security and repeatedly toured and commended;
- 2000+ agents delivered to date, accumulating on-the-ground experience in high-value markets such as public security, government, and central state-owned enterprises;
- Industry-academia-research ecosystem: co-built the “Artificial Intelligence and Cybersecurity Joint Research Center” with Huazhong University of Science and Technology, the “Artificial Intelligence Joint Innovation Laboratory” with the Suzhou Municipal Public Security Bureau, and reached strategic cooperation with several well-known vendors;
- Private delivery: offline / air-gapped deployment by default, data never leaves the enterprise, fully auditable and rollback-capable.
Technical strength and qualifications
Fully self-developed, protected by patents
- Granted invention patents
- “A cross-environment AI task collaboration execution method based on the MCP protocol” (ZL 2025 1 0655952.5) — solves the challenge of agent interoperability across environments
- “A virtualized resource scheduling method for high-concurrency AI tasks” (ZL 2025 1 0766082.9) — ensures platform performance and stability
- “A natural-language-based cross-platform intelligent task collaboration method” (ZL 2025 1 0821449.2) — improves platform usability and interaction efficiency
- Accepted invention patents: a secure privacy-preserving method based on federated cross-modal feature alignment · a malicious-traffic detection method for RDMA networks · an aggregation verification method for distributed data
- Software copyrights: AI Application Construction Platform V1.0, AI Application Enablement Platform V1.0
Xinchuang (domestic IT) and localization adaptation
The platform supports private and domestically produced deployment and has completed adaptation to mainstream domestic CPUs / GPUs and other domestic software and hardware, validated in key industries such as public security and government, meeting government and enterprise requirements for security and controllability.
Industry-academia-research and ecosystem cooperation
- Co-built the “Artificial Intelligence and Cybersecurity Joint Research Center” with Huazhong University of Science and Technology, advancing frontier research on large-model applications;
- Co-built the “Artificial Intelligence Joint Innovation Laboratory” with the Suzhou Municipal Public Security Bureau, going deep into policing operations to incubate practical public-security AI applications together;
- Reached strategic cooperation with China Mobile Hainan Company, Shenzhen Weipin Zhiyuan, Geer Software, Beijing Pentium Electronics, and others, continuously incubating scenario-based solutions.
Team and honors
- Core team: combining research backgrounds from renowned universities with industry experience at well-known companies (Huazhong University of Science and Technology, Weaver, iFlytek), forming a golden triangle of “research + technology + market”;
- Qualifications and honors: deputy secretary-general unit of the Artificial Intelligence Professional Committee of the Wuhan Cybersecurity Association; undertakes the second batch of key R&D program projects of the Wuhan Science and Technology Innovation Bureau — “key technology research and application of an agent collaboration platform for complex enterprise business scenarios.”
Closing
With fully self-developed technology as its foundation, the battle-tested TUEO intelligent foundation at its core, and deep industry-academia-research and ecosystem cooperation as its engine, Ding’an Huasheng is committed to becoming the provider of the enterprise digitalization foundation of the AI era — making AI a full-time employee of your organization, and letting every enterprise’s systems be defined, assembled, operated, and AI-enabled on this foundation.