Customer Experience

Knowledge Agent

Enterprise knowledge management and intelligent retrieval

Knowledge Agents build, maintain, and serve enterprise knowledge bases. They ingest information from every organisational source — documents, wikis, Slack channels, meetings, emails — index it semantically, keep it current, and deliver precise answers to natural language questions with source attribution and confidence scoring.

94%

Answer Accuracy

<3 sec

Time to Answer

1M+ docs

Sources Indexed

65%

Support Ticket Deflection

Core Capabilities

Multi-source knowledge ingestion — documents, wikis, Slack, email, meetings, and databases

Semantic indexing with automatic topic clustering, entity extraction, and relationship mapping

Natural language Q&A with source attribution, confidence scoring, and follow-up suggestions

Knowledge gap detection — identify topics with insufficient, outdated, or contradictory information

Access control — respect document-level permissions and security classifications in all responses

Continuous learning — automatically update knowledge as source documents change or new content is added

Use Cases

Employee knowledge access — instant answers to policy, procedure, and institutional knowledge questions

Customer-facing knowledge base — power self-service portals with intelligent search and recommendations

Onboarding — accelerate new hire ramp-up with contextual access to organisational knowledge

Expert finder — identify subject matter experts based on contribution patterns and expertise mapping

Meeting intelligence — capture, index, and retrieve insights from recorded meetings and discussions

Institutional memory — preserve and surface knowledge from departed employees and completed projects

How It Works

Ingestion & Indexing

Content is collected from connected sources via APIs and webhooks. Documents are chunked, embedded, and indexed in a vector database with metadata.

Knowledge Graph

Entities, concepts, and relationships are extracted to build a knowledge graph that enables reasoning across documents and sources.

Query Processing

Natural language questions are decomposed, relevant chunks are retrieved using hybrid search, and answers are synthesised with source citations.

Maintenance

Stale content is flagged for review. New content is indexed automatically. Conflicting information triggers human resolution workflows.

Technology Stack

Vector DBKnowledge GraphsRAG PipelineEmbedding ModelsHybrid Search

Integrations

ConfluenceNotionSharePointGoogle DriveSlackGitHub

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