Knowledge graph AI agent for product docs and support

• A knowledge graph AI agent is useful when the answer depends on relationships across docs: product area, feature, plan rule, integration, owner, exception, and latest release.
• GraphRAG is the search language people use for that pain, but the product job is simpler: selected sources become searchable graph artifacts the agent can query before it answers.
• The agent still needs boundaries. If the source material is missing or stale, it should say so instead of guessing.

The useful path is source setup, graph build, search tool, safe live checks, access, and testing.

1. 01
   Select the source set.

   Choose product docs, changelogs, pricing rules, integration guides, examples, and policies the agent is allowed to use.

2. 02
   Build the knowledge graph.

   Prostir uses ManagedCode.MarkdownLd.Kb to produce Markdown-LD and JSON-LD graph artifacts from supported source documents.

3. 03
   Enable `knowledge_search`.

   The published agent can search graph nodes, source names, headings, and relationships instead of pasting raw chunks into every prompt.

4. 04
   Add controlled tools.

   Expose only narrow live checks such as status lookup, plan lookup, integration availability, or support handoff.

5. 05
   Set access and publish.

   Publish one hosted agent with public, protected, or paid access rules and test real customer questions before sharing it.

The graph should start with approved sources, not the whole company drive.

• docdocs/product/*.mdCanonical feature pages, setup steps, limits, and known caveats.
• docrelease-notes/*.mdWhat changed, when it shipped, and which plans or regions it affects.
• datagraph.jsonldThe latest JSON-LD graph artifact the creator can inspect or download.
• codeknowledge_searchThe built-in search tool exposed only when the published agent has searchable knowledge.
• codesafe live toolsPlan lookup, status lookup, entitlement check, or support handoff with narrow schemas.

A support question spans docs, release notes, plan rules, and a live check.

• A knowledge graph AI agent is not just a chatbot over a folder. It is a hosted agent with selected sources, Markdown-LD/JSON-LD graph artifacts, `knowledge_search`, controlled tools, and access rules.
• Knowledge graph RAG is useful when questions cross document boundaries, but simple questions should stay simple and source-backed.
• Prostir keeps the graph build, endpoint, source refresh, tool boundaries, auth, quotas, and paid access attached to the same published agent.