What Is ZGI

Enterprise AI Infrastructure — Connecting Knowledge, Models, and Agent Execution

One sentence definition

ZGI is an AI agent platform for enterprise organizations, helping enterprises to unify access models, accumulate knowledge assets, orchestrate business processes, and implement AI capabilities into manageable, reusable, and integrable intelligent applications through permissions, cost, and security governance.

ZGI solves a core problem

Transform AI from a “single point tool” into a “manageable, reusable, and online enterprise capability”. If your team is also facing the problem of “AI can be used but cannot be controlled”, ZGI is born for this.

What problem does it solve?

Most companies will encounter these three typical problems when implementing AI:

1. AI assets are dispersed and difficult to precipitate

Prompt words, workflows, and knowledge bases are scattered on every employee’s computer. When employees leave, the experience is lost. When a new employee joins the company, everything starts from scratch. ZGI centrally stores all AI assets at the organizational level. The assets do not belong to individuals, but to the enterprise. They can be handed over with one click when resigning to avoid the loss of digital assets.

2. AI output is difficult to trust

Big models will “make things up with confidence.” This is almost unacceptable in scenarios such as legal, financial, and compliance where the source of the answer is highly sensitive. ZGI’s RAG engine strictly retrieves answers from the original text. Each answer will be accompanied by the source of the original paragraph (file name, page number, paragraph), allowing business personnel to quickly verify the source of the information and build trust from the source.

3. Multiple models, multiple tools, and out-of-control costs

Each department has its own set of tools, IT maintains a bunch of interfaces, and the bills cannot be understood or calculated clearly. ZGI provides a unified multi-model gateway, Token consumption is accurately attributed to each person, each department, and each application, and a complete cost management closed loop is formed through workspace quota, API Key quota, and monthly statistics.

Core Competencies at a Glance

• Agent Orchestration: Visual workflow canvas, drag and drop nodes to build multi-step AI applications
• Enterprise-level knowledge base: RAG + enhanced knowledge graph, each answer comes with the source of the original paragraph
• Database & NL2SQL: Intelligent generation of table structures from business documents, natural language query data
• Unified Model Gateway: official channel + private channel, one interface calls all models
• Permission and Fee Center: RBAC + workspace quota + API Key + billing flow
• Flexible deployment: Cloud SaaS is ready to use, and private deployment data does not leave the domain.

4 ways for developers to integrate

• REST API — OpenAI compatible interface, knowledge base query, Agent call, workflow triggering

• Webhook — real-time push of workflow execution results, access to OA / ERP / CRM in 5 minutes

• Python/JS SDK — Official SDK, ready to use out of the box

• SSO single sign-on — LDAP, SAML 2.0, OAuth 2.0 (Feishu / DingTalk / Enterprise WeChat)

Next step

• 30 Minutes Quick Start — Run through your first ZGI AI application from scratch
• Core Concept — Relationship between workspace, agent, knowledge base, model, and permissions
• Product Architecture — ZGI’s six major product features and base design