AI Support
Lexul AI Support Knowledge Base
Optimized Fumadocs structure for a Lexul customer support AI agent.
Audience: Lexul customer support AI agent, onboarding team, support team, and documentation maintainers.
Use: Host this folder in Fumadocs. Configure the AI agent to retrieve only the needed group page or individual### Knowledge Record:chunks.
What changed
This package splits the previous single chatbot training page into standalone feature-group routes. This improves retrieval efficiency because the AI agent can load only the relevant feature group instead of reading the full knowledge base.
Recommended retrieval flow
- Classify the user's request into one or more intents from Schema and Routing.
- Match the request to a feature group page.
- Retrieve the top one to five
### Knowledge Record:chunks from that page. - Answer using Agent Instructions and the retrieved records.
- Escalate when the record's
escalation_ruleapplies or when retrieved records do not confirm the requested behavior.
Page map
| Page | Purpose |
|---|---|
| Agent Instructions | Short system-style behavior profile for the support bot. |
| Schema and Routing | 20-field documentation schema, intent labels, record format, and chunking rules. |
| Feature Groups | Index of feature-group knowledge pages. |
| Source Index | Lexul.com and help.lexul.com URLs used by the training records. |
| Ingestion and Evaluation | Metadata recommendations and chatbot evaluation checklist. |
Feature group retrieval sizes
Use this table to decide how much context to retrieve. Token counts are approximate and assume roughly four characters per token.
| Feature group | Records | Approx. page tokens |
|---|---|---|
| Customers | 10 | ~7,118 |
| Assets | 7 | ~5,005 |
| Sales | 4 | ~2,968 |
| Deals | 2 | ~1,145 |
| Contracts | 6 | ~4,072 |
| Inventory | 6 | ~5,177 |
| Equipment | 2 | ~1,462 |
| Inspections | 3 | ~1,909 |
| Receipts | 2 | ~1,385 |
| Timesheets | 3 | ~2,173 |
| Users | 2 | ~1,416 |
| Time Tracking | 5 | ~3,337 |
Packaging notes
- Generated:
2026-06-23 - Content format: Fumadocs-compatible MDX
- Chunking target: one
### Knowledge Record:per vector record - Best production use: retrieve by feature group first, then by record-level semantic similarity