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Zhixu, AI system architecture

AI SYSTEM

Enterprise knowledge base and AI agents, closing the loop on tasks.

Design permission-controlled knowledge bases, multi-model and tool orchestration, agent task flows, and API integration, so AI connects to real business.

Guanche, AI scenario insight

From enterprise knowledge to agent task loops

Systems should not only generate answers but also call tools, drive tasks, and report results within permission and audit boundaries.

Knowledge foundation

Unified sources, layered permissions, update mechanisms, and citation traceability.

Agent workflows

Define task steps, tool calls, failure rollback, and human confirmation.

System Integration

Connect accounts, APIs, data storage, and existing business processes.

Quality evaluation

Continuously evaluate correctness, completion rate, latency, cost, and risk.

Huguang, spatial intelligence guide

Enterprise knowledge base and agent delivery content

Deliver knowledge permission structures, agent workflows, tool and API connections, and traceable evaluation mechanisms.

Enterprise knowledge base and permissions
Multi-model and tool orchestration
Agent task flows
Business system and API integration

First connect one task chain, then expand system scope

Business owners prepare to authorize knowledge sources, role permission tables, API documentation, test environments, and representative task samples. Key write operations and external actions require separate confirmation.

Implementation work

Establish source-permission mapping, data integration and update mechanisms, encapsulate tool parameters and error results, and design task status, manual approval, duplicate execution prevention, and audit trails.

Acceptance evidence

Use fixed normal and exception samples to check references, task completion, access results for different roles, tool failure fallback, and manual takeover. Keep versions, input/output, and unresolved issues.

Clear boundaries

The knowledge base cannot fabricate missing information, and the agent cannot obtain permissions beyond business authorization. Whether third-party interfaces, licenses, and core system modifications are included needs to be confirmed in the blueprint.

Common questions about knowledge base and agents

Does more data always mean better results?

Not necessarily. Authority, scope, version, and permissions matter more than volume. Clean up conflicts and establish a representative problem set first, then expand gradually.

Can it automatically perform business operations?

It can be designed within clearly authorized scopes, but high-risk or irreversible operations should keep human approval, audit trails, and failure rollback. Read-only validation first usually makes it easier to confirm value.

What if existing systems have no API?

First evaluate legal and authorized data exports, standard interfaces, or other supported methods. We cannot promise stable automatic operation for any system; limitations will be included in the proposal.

Lixing, FDE Pre-Deployment Engineering

Submit project background

Describe the goals, current state, and expected timeline, and we will organize the next steps accordingly.