Pet policy from approved document
Scenario: Visitor asks, “Do you allow small dogs?”
System behavior: AI retrieves the active pet policy document for that community.
Result: AI drafts or sends a property-accurate response based on configuration.
Document Center / AI Knowledge Base
The Document Center gives each PMC/community a controlled place to manage the documents and approved URLs that staff and AI rely on: pricing, policies, brochures, floor plans, care/service information, move-in requirements, FAQs, amenities, and promotions.
Sales directors often maintain the same information across multiple places: websites, brochures, APFM/Caring profiles, internal folders, email attachments, and spreadsheets. This creates inconsistent information and weak AI accuracy.
The Document Center solves this by becoming Journey’s approved property knowledge layer. It is not just file storage; it is the operational knowledge base that powers response drafting, AI chat, internal lookup, onboarding readiness, custom reports, and third-party content consistency.
URL ingestion should be controlled. Customers provide approved URLs; Journey fetches, extracts, sanitizes, and indexes the content only after validation.
flowchart TD
A[Admin opens Document Center] --> B{Source Type}
B -->|File Upload| C[Upload file]
B -->|Approved URL| D[Add URL]
C --> E[Select category + PMC/community/property]
D --> E
E --> F[Store file or URL metadata]
F --> G[Extract text / scrape page]
G --> H[Sanitize + redact unsafe content]
H --> I[Chunk + create embeddings]
I --> J[Vector search index]
J --> K[Mark AI Indexed]
K --> L[AI retrieval for drafts, chat, reports, lookup]
Required planning item: Develop Document Center UI and workflow plan.
Required planning item: Define Document Center versioning/update plan.
| Item | Plan |
|---|---|
| File replacement | Creates a new version. Previous versions become archived unless restored. |
| URL refresh | Stores last fetched content version and timestamp. |
| Active version | Only active approved version is used by AI retrieval. |
| Last indexed date | Shows whether AI search is current. |
| Freshness alerts | Pricing/policy docs can be flagged for periodic review. |
| Rollback | Authorized user can restore a previous version if needed. |
Before content is indexed for AI, the system should sanitize and validate extracted text.
Required planning item: Include S3 + vector search + PMC/community isolation.
flowchart LR A[Document Center UI] --> B[Metadata Service] B --> C[(Document Metadata DB)] B --> D[S3 Secure File Storage] B --> E[Approved URL Registry] D --> F[Extraction Worker] E --> G[URL Fetch + Scrape Worker] F --> H[Sanitization + Chunking] G --> H H --> I[Embeddings] I --> J[(Vector Search Index)] C --> K[Scoped Retrieval Filter] J --> K K --> L[Response Drafting] K --> M[AI Chat Widget] K --> N[Internal Knowledge Lookup]
Draft responses grounded in current approved pricing, policy, and amenity documents.
Website assistant answers common questions using property-scoped Document Center content.
Reports can summarize document readiness and highlight stale property knowledge.
New communities can be checked for required documents before AI enablement.
Scenario: Visitor asks, “Do you allow small dogs?”
System behavior: AI retrieves the active pet policy document for that community.
Result: AI drafts or sends a property-accurate response based on configuration.
Scenario: Customer maintains amenity details on their property website.
System behavior: Approved URL is re-scraped, sanitized, and indexed.
Result: AI uses fresh website content without manual PDF upload.
Scenario: Pricing sheet has not been updated in 90 days.
System behavior: Document Center flags the file for review.
Result: AI can be restricted from quoting stale pricing until updated.