AI, Engineered for Government

Private deployment by default: models and data run entirely in your environment — on-premise, government cloud or private network. Data never leaves your environment or jurisdiction. Access is role-based with auditable logs, security review precedes launch, and we support local security assessments.

Yes. We work with domestic chips, servers, operating systems and databases, with model inference adapted to domestic compute. Exact combinations are confirmed item by item after on-site research and written into the technical proposal.

Three models are supported: on-premise, government cloud, or private network. An LLM appliance is also available, with compute delivered alongside the hardware, so no environment preparation is needed. For existing data centers, our on-site survey assesses compute, network and security conditions and defines an adaptation plan; interface lists and retrofit scope are confirmed in writing during solution design.

No rip-and-replace. We integrate through standard interfaces and data exchange, building incrementally on your existing IT investments. Scope, interface lists and responsibility boundaries are confirmed in writing during solution design.

The standard path is consulting & diagnosis, solution design, build & implement, and continuous operation. We start with high-frequency, verifiable scenarios — the first one typically reaches acceptance within 3 months, with KPIs jointly agreed in the contract.

Core engineers can be stationed at your location long-term, working face-to-face with your staff. They follow your confidentiality and security rules, and can sign NDAs and complete background checks.

Training is a standard deliverable: system usage training plus model operations and continuous iteration training, along with deployment guides, operations documentation and reproduction steps. After launch, the on-site team provides hands-on support for a period; routine operations are handled independently by your staff, while complex tuning remains our responsibility.

Models are domain-trained on your policies, knowledge and historical data, with sourced answers. During operation we continuously enrich knowledge and tune performance; uncertain cases escalate to humans and feed back into improvements.

Interfaces and documentation support Chinese, English and other major languages; models can be trained on your multilingual corpus for multi-ethnic regions and international-facing services.

Efficiency, accuracy and satisfaction metrics are jointly confirmed and written into the contract, with milestone-based acceptance. You scale investment only after pilot acceptance — avoiding large upfront risk.

Yes. We follow public procurement processes, providing qualification documents, bid materials and Q&A support. Commercial form (project-based, annual service, etc.) and payment milestones are confirmed together during solution discussions.

System code and documentation from custom development are delivered with the project; model weights, adapters and inference services from training belong to you; business data runs and stays in your environment throughout. Ownership of each item is specified in the contract.

Every project includes a warranty period and maintenance support: defects are fixed free of charge during warranty, with response times written into the contract. On-site or local support teams remain after launch, and issues during on-site periods are handled first. Warranty length and maintenance scope are defined per project in the contract.

We design this risk out from the start: the first scenario typically reaches acceptance within 3 months, with KPIs jointly agreed and written into the contract. Investment is staged — prove first, scale later — and if the pilot falls short, we follow the contract rather than scaling unproven spend.