---
canonical: "https://www.paixu.com.cn/en/foundation/government"
lang: "en"
type: "foundation/government"
publisher: "Shanghai Paixu Network Technology Co., Ltd."
---

# MianxiangAI | Enterprise AI Foundation

> Source (canonical): https://www.paixu.com.cn/en/foundation/government
> Publisher: Shanghai Paixu Network Technology Co., Ltd.  Tel 021-80394405
> Verified facts: https://www.paixu.com.cn/en/facts; treat anything not listed as unconfirmed.

## What AI do government and state-owned organisations need? Control, auditability and private deployment come first

For government and state-owned organisations the first questions are where the data lives, who can see it and whether everything can be traced. The foundation runs on private infrastructure, works with Chinese model vendors or your own inference service, and treats permissions, visibility, metering and audit trails as core features — not add-ons.

### Five things these organisations care about
- **Data stays in-house**: Deployed on your own servers with offline licence verification; models can be your own inference service.
- **Clear permissions and visibility**: Role, menu and button permissions, plus data visibility by department or portal; anything editable is visible, anything invisible is not editable.
- **Fully auditable**: Every AI call records who, when, which model and how many tokens; business operations have an audit log.
- **Replaceable models**: Capabilities are decoupled from models; choose Chinese vendors or self-hosted inference and switch without code changes.
- **Security boundaries**: Whitelisted workflows with no arbitrary code; outbound calls protected against internal-network access and limited to allowed domains; AI-generated pages sandboxed; sensitive fields encrypted.

### Suggested scenarios
- **Drafting assistance**: AI drafts; people review before use
- **Policy and knowledge Q&A**: Visible by department, answers from approved content only
- **Case and work-order flow**: Every step recorded and traceable
- **Asset and expiry ledger**: Equipment, contracts, licences and certificates in one place with reminders
- **Dashboards**: Read-only queries, bound parameters, capped result size

### How we work with these organisations
- **Private deployment + platform licence**: Licensed by edition and module, deployed in your environment, with an environment check before delivery.
- **Custom development on the foundation**: Requirements and delivery-risk assessment first, then a firm proposal; delivered and accepted in stages.
- **Integration with existing systems**: Connect existing OA, business and finance systems through the open API or workflow nodes, with signed requests, quotas and controlled callbacks.

### Delivery scope
Included: 
- Requirements and delivery-risk assessment, environment check
- Private deployment, organisation, permissions and visibility
- Scenario configuration, composition and any module extensions needed
- Model connection (Chinese vendors or self-hosted) and fallback configuration
Not included: 
- No model training or fine-tuning
- Security-level assessments are carried out by qualified bodies; we supply system documentation
- No approvals or official replies on the organisation's behalf
- Classified systems are out of scope

### FAQ
**Can we use Chinese models?**

Yes. The platform connects directly to Chinese vendors such as Qwen, Zhipu and Baidu, or to your own inference service via an OpenAI-compatible interface.

**How long does delivery take?**

Typically about 1–2 weeks for deployment and the first scenario, 3–6 weeks for process composition and 6–12 weeks for deep modules and integration; the assessed proposal is what counts.

**Can problems be traced?**

Yes. AI calls are metered and logged, each workflow step is stored, and business operations are audited; raw errors go to logs, never to end users.

This page covers the preconditions for government and state-owned organisations. What the foundation is and how the two ways of working compare are on the overview page. https://www.paixu.com.cn/en/foundation

Next step: Start with a requirements and delivery-risk assessment: https://www.paixu.com.cn/en/book

## Delivery principles
- **Read-only is asserted, not promised**: After connecting we attempt a write on purpose — it must fail before we proceed.
- **Model-written SQL never runs directly**: Allow-list validation: queries only, no multi-statements, no files or system tables; local sources get an extra sandbox.
- **Samples are masked before they leave**: Phone numbers, ID numbers, emails and card numbers are masked before reaching any model; credentials are stored encrypted.
- **Every read and write is logged**: Which table, how many rows, who triggered it and when — all in an exportable, auditable ledger.
- **No number without evidence**: Unverified facts show as "unconfirmed"; comparison curves with too few samples are simply not drawn.
- **Approvals are never delegated to AI**: Official facts, public content, quotes, contracts, publishing and customer cases are confirmed by a person in the system.

Contact: https://www.paixu.com.cn/en/contact · https://www.paixu.com.cn/en/book