Turn Fragmented Enterprise Content Into Trusted, Source-Linked Answers

The search problem

• Users do not know the exact terminology
• Important content exists across multiple repositories
• Traditional search returns long lists of weak results
• Duplicate and outdated pages compete with authoritative content
• PDFs and documents are difficult to navigate
• Employees repeatedly answer the same questions
• Public users abandon tasks
• Search teams lack insight into failed searches

Search experience

Core capabilities

• Natural-language questions
• Keyword & semantic retrieval
• Federated search
• Website & CMS indexing
• Document indexing
• Metadata & taxonomy
• Synonym management
• Typo tolerance
• Faceted filters
• Permissions-aware results
• Source citations
• Extracted answer passages
• Confidence thresholds
• Related questions
• Recommended services
• Multilingual retrieval
• Accessible search
• Search analytics
• Zero-result analysis
• Content-gap identification
• Feedback & answer review
• Administrative tuning
• Content freshness controls

Grounded AI architecture

Answers are generated from approved, indexed sources rather than unrestricted model memory. AI output can still be inaccurate — which is why confidence thresholds, source visibility, human review and escalation to official contact channels are built in.

1. 1

   Connect approved content

   Authorize and connect websites, CMS, documents and approved enterprise systems.

2. 2

   Parse and classify

   Extract text, structure and metadata; classify content for retrieval.

3. 3

   Index and secure

   Build a permissions-aware index that preserves source-system access.

4. 4

   Retrieve relevant evidence

   Retrieve the most relevant passages with confidence scoring.

5. 5

   Generate an answer with source links

   Produce a grounded answer with citations only to approved sources.

When evidence is insufficient, the system falls back to a clear "no confident answer" response with a path to official contact channels — rather than generating an unsupported answer.

Permissions and security

Enterprise deployments can preserve source-system access permissions so users receive only content they are authorized to access. This capability is deployment-dependent — it requires identity integration and per-repository permission mapping.

• Role-based access
• Identity integration
• Repository permissions
• Query logging
• Administrative controls
• Sensitive-content exclusions
• Retention controls
• Environment separation
• Model & provider configuration

Whether customer data is used for model training is determined by the actual deployment and contractual configuration — Lizentia does not make unverified claims about training use.

Public website use cases

• Government service discovery
• Policy & regulation search
• University program search
• Resident & constituent questions
• Public document search
• Forms & application guidance
• Procurement-resource search
• Department & contact discovery

Internal enterprise use cases

• Policy search
• Employee knowledge
• Legal knowledge
• Technical documentation
• Procedures
• Support knowledge
• Contract repositories
• Project documentation
• Research & institutional knowledge

Search governance

• Source approval
• Content ownership
• Indexing schedules
• Stale-content rules
• Restricted content
• Answer evaluation
• Query review
• Feedback management
• Model changes
• Risk review
• Audit history

Analytics

• Most frequent queries
• Failed queries
• Zero-result searches
• Low-confidence questions
• Unused content
• Content gaps
• Search refinements
• User feedback
• Search-to-action conversion
• Department-level trends

Integration options

Scope-dependent integration with:

• Public websites
• CMS platforms
• Intranets
• Document-management systems
• Knowledge bases
• Cloud storage
• CRM systems
• Case-management platforms
• Service portals
• Data warehouses
• Approved APIs

Deployment process

1. 1Content & use-case discovery
2. 2Source & permission mapping
3. 3Search experience design
4. 4Index & retrieval configuration
5. 5AI governance & evaluation
6. 6Pilot deployment
7. 7Production launch
8. 8Continuous optimization