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SpectronTrust every fact with complete provenance and seamless hybrid retrieval

Spectron delivers ACID agent memory with provenance tracking, hybrid retrieval, and tri-temporal facts. One substrate for graphs, vectors, documents—no sync pipelines needed.

Agent Memory Systems
Knowledge Graph
Vector Database
Spectron screenshot

More About Spectron

Spectron

Spectron is the persistent, queryable memory layer for AI agents that you can actually trust. Built on SurrealDB's multi-model foundation, it unifies documents, graphs, vectors, and structured records in one ACID transaction—eliminating the consistency gaps and black-box retrieval that plague stitched-together memory middleware.

Product Highlights

  • ACID-Transactional Memory: Graph, vector, document, and structured records commit atomically in one transaction—no cross-store stitching, no silent data loss
  • Supersession-Based Updates: Facts are never overwritten; they are superseded with full provenance preserved, so agents always know what changed and when
  • Eight-Signal Hybrid Retrieval: Combines embeddings, BM25, graph traversal, keyword bridges, PageRank, geographic recall, and trace-derived features into one auditable ranking
  • Tri-Temporal Tracking: System time, known time, and valid time are stored separately—answer "what did we believe then?" not just "what do we believe now?"
  • MCP-Native Integration: Built-in Model Context Protocol server connects directly to Cursor, Claude Desktop, and Claude Code with zero configuration

Use Cases

  • Conversational AI Agents: Long-running assistants that remember user preferences, past decisions, and evolving context across months of interaction
  • Enterprise Knowledge Systems: Grounded retrieval from authoritative documents with full citation chains and uncertainty handling for compliance-critical domains
  • Multi-Agent Collaboration: Shared, reconcilable memory across agent fleets with scope isolation, corroboration thresholds, and collective belief crystallization
  • Autonomous Decision Systems: Self-improving memory through reflection, elaboration, and consolidation that deepens understanding between interactions

Target Audience

Spectron serves AI engineers and platform teams building production-grade agent systems where memory failures are unacceptable—particularly in regulated industries like finance, healthcare, and defense where provenance, auditability, and temporal accuracy are non-negotiable.

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