Graphiti

Citation Needed: Provenance for LLM-Built Knowledge Graphs — Daniel Chalef, Zep AI

Jul 23, 2026 · 20:54

Daniel Chalef argues that provenance for knowledge graphs built by LLMs must itself be a graph, not a simple source ID, because LLM synthesis destroys the paper trail. In Graphiti, the open-source temporal graph framework behind Zep, sources become episodes and derived facts link back to them, enabling a graph walk to trace any fact. This handles merges (merged entities keep all source links), invalidation (invalid-at dates on mutated edges), and metadata projection (tags on episodes inherit to derived facts). Deletion follows the same edges: a fact survives GDPR erasure only if other supporting episodes remain. Benefits include compliance, veracity evaluation, and debuggability for agentic systems.

Memory Masterclass: Make Your AI Agents Remember What They Do! — Mark Bain, AIUS

Jun 27, 2025 · 51:25

Mark Bain, Vasilia Markovits, Alex Gilmore, and Daniel Chalev demonstrate that AI memory requires causal relationships and graph databases, not just vector similarity, to solve hallucinations and enable agentic workflows. Bain argues that memory is any data affecting change, and that attention, diffusion, and VAEs follow the same geometric principles as gravity and entropy. Alex shows Neo4j's MCP server storing semantic memory as entities and relationships retrieved across conversations. Vasilia demos Cognee building semantic graphs from GitHub data for agentic hiring decisions. Daniel presents Graphiti's domain-aware memory using custom Pydantic schemas to filter irrelevant facts. Bain introduces a GraphRAG chat arena that switches between memory solutions on a single Neo4j graph, testing different implementations for episodic and temporal recall.