Building Knowledge Graphs & Wiki from Enterprise Docs with Alibaba Cloud Milvus

An office equipment vendor's customer service receives a query: a laptop bought 18 months ago has a battery that won't charge. The whole unit is under warranty, but the battery may have a different coverage period. The agent must check the product manual, warranty terms, service coverage, and application guide — information scattered across multiple documents.

Alibaba Cloud's vector retrieval service Milvus provides a knowledge construction capability that organizes enterprise documents into a sourced knowledge graph and Wiki. These can be used for retrieval and AI question answering, allowing teams to verify, read, and maintain knowledge repeatedly.

01 Import Product Manuals, Warranty Policies, and Service Guides

After preparing the knowledge base and model configuration, go to

Milvus Console → Knowledge Base → Target Knowledge Base → Data Management

and import the product description, warranty terms, service scope, and application guide. Once parsing completes, spot-check key clauses in Chunk Management to confirm that validity periods, applicable objects, and service conditions are correctly identified. Both the graph and the Wiki will be built around this knowledge base, giving customer service a reusable reference for recurring inquiries.

02 Define Ontology Objects and Relationships; Graph Shows Concrete Warranty Clauses

An ontology defines the business objects, attributes, and relationships. In Milvus knowledge construction, this is done through the graph schema. For the example, the following definitions are used:

Object types: Product, Component, Warranty Clause, Service, Region

Attributes: Warranty months, calculation basis, appointment requirements

Relationships: Product → contains → Component; Product or Component → applies to → Clause; Service → covers → Region

You can start from the default General Graph template or use Manage Graph Schema and Rules → AI Generate by entering business goals or referencing knowledge base materials. After generation, click Use Result, review, adjust, Save Settings, then Build Graph.

Once built, open Knowledge Graph, search for "Battery". The left sidebar locates the object, the central canvas shows relationships, and the right panel displays description, attributes, applicable clauses, and source references. In this case, the battery links to a 12-month warranty clause, while the whole laptop links to a 24-month clause. The agent can verify each basis separately and follow relationships to see Hangzhou on-site service and required application materials, avoiding incorrectly applying the whole-unit period to the battery.

03 Organize Clauses and Processing Requirements into a Team Wiki

The Wiki structures materials into interlinked topic articles for continuous reading and manual revision. It can be built independently without completing the graph first. In Knowledge Construction, click Build Wiki → Start Building; by default it uses All parsed and enabled documents with no template adjustment needed. After building, click View Result, select an article from the table of contents, expand Reference Sources to compare with original text, and click Edit Article → Save and Update to revise.

Using the default template, the example generates two linked entries: "Office Laptop" and "Device After-sales Application". One segment states: "If a specific component in the device has a separate warranty period, prioritize verification according to that component's clause." The entire after-sales process can be organized by themes such as product policy, handling requirements, and service fees. When source documents change, update the originals and rebuild; manual edits are not overwritten automatically — merge suggestions let you keep, adopt, or combine changes.

04 Let the Graph and Wiki Answer the After-sales Query Together

After both graph and Wiki are built and verified, enter Dialogue, choose an available chat model, select version Draft, and enable Knowledge Graph and/or Use Wiki. Then input the original query. The answer must address three points: whether the battery is still under warranty, conditions for Hangzhou on-site service, and how to submit the application. Open citations to confirm each conclusion maps to the original source.

The Q&A combines object relationships from the graph, processing flows from the Wiki, and original clauses. Via the knowledge base Q&A API, technical teams can integrate this capability into customer service assistants or internal business applications.

05 Turn Enterprise Documents into Knowledge Graphs and Team Wikis

Use ontology to define business objects, graphs to verify concrete facts, Wikis to organize team guides, and let all of them ground AI answers. Alibaba Cloud Milvus knowledge construction makes product manuals, service policies, and internal materials repeatedly consultable, maintainable, and usable by teams.

Pick a document category your team frequently cross-checks, build your own knowledge graph or Wiki, and test with a real question.