Not a database.
A gravitational
system.
Every memory has a gravity score. High-gravity memories orbit close to their cluster. Low-gravity memories drift to the periphery. The nightly engine recalculates everything.
What you see in the background is a live simulation of the substrate topology — clusters, memories, and the relationships binding them.
What enters the substrate.
How it gets there.
Every signal — real-time chat, imported history, agent findings, corrections — passes through the same five-stage ingestion pipeline before being written to the substrate. No exceptions. No shortcuts.
Entity. Temporal. Well. Topic.
All four. Simultaneously.
Retrieval runs across four independent dimensions — none of which is a standard vector search. The five-axis scoring engine in the kernel uses these four dimensions as inputs. This is where “compounding” becomes structural, not metaphorical.
01
Entity Axis
WhoRecall surfaces everything connected to a specific entity — people, organizations, projects, concepts. Alias resolution ensures the graph is complete, not fragmented by name variation.
02
Temporal Axis
WhenTime-scoped retrieval. Recent context weighted differently from longitudinal. The system knows the difference between a decision made last week and a pattern established over six months.
03
Well Axis
DepthThe Gravity Well score — a composite of frequency, recency, emotional density, and outcome correlation. Deep wells surface first. Shallow wells only when directly relevant.
04
Topic Axis
WhatSemantic topic clustering. Vector similarity anchors retrieval to a concept space, then structural and relational signals amplify the most operationally significant results within that space.
Memories organize.
Clusters compound.
Individual memories are assigned to Knowledge Clusters — topic groupings with measured cohesion, leakage, drift, and salience. A cluster isn't a folder. It's a living structure with health metrics, recalculated every night by the engine.
Cohesion
0.84
Average membership strength across all nodes in the cluster. High cohesion = tight, operationally specific topic.
Leakage
4.2%
Percentage of cluster members below the gravity threshold. Managed nightly — leaking members pruned or reassigned.
Drift
0.11
Rate at which the cluster centroid is shifting topic-wise. High drift triggers canonical summary regeneration.
Salience
0.91
Composite score used by five-axis retrieval. Determines whether the cluster amplifies or attenuates individual memory scores.
04 — Gravity Weighting
Not all memory is equal.
Gravity decides what surfaces.
Every memory has a gravity score — a composite of frequency, recency, emotional density, and outcome correlation. High-gravity memories surface first in retrieval. Low-gravity memories require direct relevance before they appear.
The nightly engine recalculates total_gravity and active_gravity for every memory in every cluster that drifted more than 0.5 since the last cycle.
Gravity score examples — same substrate
One flag.
Immediate propagation.
When a user marks something incorrect, the correction doesn't just suppress a single memory — it propagates through the graph. Gravity is adjusted. Context flags are set. Affected clusters are queued for recalculation. Five steps. Real-time.