Last time, ENGRAM handed a person the power to make agents — fenced. This release hands a bounded slice of that power to an agent itself: with a human’s say-so, an orchestrator can become a manager, spin up a small team of sub-agents — each a distinct identity with its own memory — fan work out to them, and gather it back. Not a control plane bolted on top; the team thinks together through the same memory it already had. A team of its own, bounded at every edge.
Tag: graphrag
A Brain Between Sessions — and Between Agents: ENGRAM Learns to Recall on Demand
The last release let ENGRAM be told what to keep and to lend a slice of it to someone I named. This one gives it the other half of the gesture: a way to deliberately reach for what it knows. An agent can now recall its own memory across sessions — a brain it keeps for itself, needing nothing switched on — and, when I’ve shared something to it, reach for that too. Private by default, as ever: my own memory is always mine to recall, and a borrowed memory is only ever what someone named for me.
Completing the Mind: ENGRAM Now Remembers Conversations from Claude Desktop, ChatGPT, and Gemini
ENGRAM already remembered my articles and my code sessions. The last missing piece was the work I do with assistants … More
Claude Code and ENGRAM Knowledge Hub: recalling the good memories together
This is a follow-up post about the next layer of knowledge consolidation in ENGRAM Knowledge Hub. Ingestion of Claude Code sessions into the Knowledge Hub allowed me to close the gap between what I researched and planned and what I actually built, including the changes, feature design enhancements, and pivots that often happen during development.
When Graphs Remember Better Than Summaries
How hippocampal-inspired memory consolidation and Personalized PageRank give AI assistants structured recall across conversations and documents. Why We Built ENGRAM … More
ENGRAM Part 3: Hippocampal-Inspired Memory – Working Memory, Long-Term Memory, and Periodic Consolidation
How ENGRAM’s agents remember what matters across multi-turn research sessions, and how memory biases retrieval toward coherent results Introduction In … More
ENGRAM Part 1: GraphRAG with Hippocampal-Like Associative Retrieval
Part 1 of this blog series explains how query-entity relevance spreading across a knowledge graph eliminates the need of typical … More
GraphRAG Part 2 – Cross-Doc & Sub-graph Extraction, Multi-Vector Entity Representation
Part 2: A deep dive into implementation of cross-documents semantic relations extraction, multi-hop graph traversal queries, and multi-vector (entities, relations, … More
Building a GraphRAG System – Core Infrastructure & Document Ingestion
Part 1: A deep dive into multi-database architecture, AI-powered entity extraction, and intelligent document processing Introduction Traditional RAG systems rely … More