Solve the core problems of enterprise data use
Knowledge silos
Knowledge is scattered across personal devices, drives and business systems.
Stale indexes
Documents change continuously without a dependable update mechanism.
Untraceable answers
Answers without citations are difficult to verify and trust.
Core Capabilities
Composable capabilities adapt to different organizations, industries and deployment environments.
Document understanding
Parse common office formats and complex layouts while preserving structure and source context.
- OCR
- Layout parsing
Traceable segmentation
Create knowledge chunks using headings, paragraphs and semantic boundaries with source metadata.
- Semantic chunking
- Metadata
Hybrid retrieval
Combine keyword and vector retrieval, rerank results and retain source citations.
- Hybrid search
- Reranking
Permission-aware answers
Reuse organizational and document permissions to control retrieval and answer scope.
- Permission inheritance
- Isolation
Platform Architecture
- Knowledge SourcesPolicies, manuals and business documents
- ProcessingParse, clean and segment intelligently
- Knowledge LayerIndexes, vectors and metadata
- RetrievalRecall, reranking and permission filters
- ApplicationsQ&A, assistants and embedded experiences
Integration Methods
- Connect data through supported connectors, files, object storage or controlled APIs after a technical assessment.
- Integrate with enterprise identity, access and logging systems to preserve existing security boundaries.
Security & Deployment
- Evaluate private, dedicated or controlled cloud deployment according to data sensitivity and network boundaries.
- Confirm access filtering, audit logs, secrets and storage policies before the proof of concept.
Verifiable Evidence & Limits
These are checkable acceptance signals and explicit boundaries—not unverified performance promises.
Acceptance Evidence
- Validate the implementation with traceable sources, permission tests and documented acceptance criteria.
- Measure coverage, update freshness and task completion against an agreed test set.
Capability Limits
- Results depend on source quality, metadata completeness, permissions and update processes.
- High-impact decisions and actions require explicit controls and human review.
Frequently Asked Questions
- How should an organization start with AI Knowledge Base?
- Start with one high-value workflow, a defined user group, known data sources and measurable acceptance criteria, then expand after testing quality and security.