Memento
Knowledge & Data
Mission impact
Institutional knowledge is only an asset when the right answer reaches the right person at the moment it is needed. By consolidating scattered documents, records, and expertise into a single governed source of truth — and pairing high-performance search with retrieval-augmented AI that returns answers rather than document lists — Memento removes the hours teams lose reconstructing what the organization already knows. Decisions proceed on complete information, new personnel reach proficiency sooner, and expertise no longer departs with the individual who held it.
Memento is the Wilkes & Liberty knowledge and data platform — high-performance search and retrieval-augmented AI over a sovereign data foundation, turning your organization's scattered documents, records, and institutional knowledge into a single, fast, intelligent source of truth.
Teams find the right answer, not just the right document: every response is grounded in sources your organization holds, need-to-know access is enforced at query time, and nothing leaves your boundary to be indexed by someone else. The result is less time spent searching and faster, better-supported decisions.
The Manifest data layer
Underneath the knowledge surface, Memento's Manifest data layer provides the machine-facing foundation: structured storage, pipelines, and retention under your control, plus durable context and state for agentic systems — what an agent knew, decided, and did persists in storage you own and can audit. People get a knowledge surface to search and ask; applications and AI agents get the persistent memory they depend on — one platform serving both audiences, entirely inside your boundary.
Key capabilities
Intelligent full-text and faceted search
Intelligent full-text and faceted search
Multilingual and secure search indexing
Multilingual and secure search indexing
Real-time synchronization and relevance tuning
Real-time synchronization and relevance tuning
Integration with existing content systems
Integration with existing content systems