MemCube v4.1 and SMRS v1.0 — formal specifications for interoperable, provably safe agent memory governance.
A standardized JSON Schema for AI agent memory entries. Designed for interoperability across LangChain, CrewAI, AutoGen, LangGraph, mem0, and any agent framework.
| Field | Type | Description |
|---|---|---|
| id | string | Unique identifier |
| content | string | Memory content text |
| type | enum | One of 7 memory types |
| timestamp_age_days | float | Age in days since creation |
| source_trust | float 0-1 | Source reliability score |
| source_conflict | float 0-1 | Contradiction level with other sources |
| downstream_count | int | Number of dependent agents |
{
"id": "mem_001",
"content": "User prefers wire transfers under $10,000",
"type": "preference",
"timestamp_age_days": 14,
"source_trust": 0.91,
"source_conflict": 0.04,
"downstream_count": 3
}
A formal risk scoring standard for AI agent memory validation. Computes a 0-100 risk score from 10 components, producing one of four preflight decisions.
Sgraal returns one of four decisions per preflight call. Concrete numerical band cutpoints are tenant-specific and recalibrated continuously — only the qualitative semantics are part of the public standard.
USE_MEMORY
Safe to proceed
WARN
Proceed with caution
ASK_USER
Human approval needed
BLOCK
Do not proceed
s_freshness
Memory age decay
s_drift
Semantic drift
s_provenance
Source reliability
s_propagation
Blast radius
r_recall
Recall accuracy
r_encode
Encoding quality
s_interference
Cross-entry conflict
s_recovery
Recovery capability
r_belief
Model belief alignment
s_relevance
Intent-drift detection
Standard body: Sgraal Governance Working Group · Version: SMRS v1.0
Joint benchmark with Grok (xAI)
1.000
F1 Score
Across all 3 corpora
239/239
Corpus Cases
All green on live API
0
False Negatives
No unsafe memory passed through
These figures reflect synthetic R12/R14 corpus performance; production calibration is pending paying-customer onboarding.
For Regulators
Regulators need reference implementations and standards specifications to enforce AI accountability. The Sgraal protocol could become an industry standard — we welcome regulator engagement, working group seats, and RFC participation.
A reference deployment of the AI decision recorder pattern — deterministic replay, signed evidence, court-admissible artefacts. Designed to be cited in regulatory guidance rather than to compete with regulator-developed alternatives.
Formal specification document for the memory governance protocol — published openly, open to comment, structured for standards-body submission. The draft is in active development; we welcome regulator review.
We are interested in participating in working groups and responding to RFCs related to AI memory governance, EU AI Act enforcement, and emerging accountability standards.
If you represent a regulator, supervisory authority, or standards body and want to discuss AI memory governance, the reference implementations above, or the draft specification — email below. We respond.
Email the regulator desk →No demo calls or sales follow-ups. Regulator engagement, not vendor pitching.
No signup needed. Use the demo key to try the full 87-module safety pipeline.
Demo key: sg_demo_playground — no signup needed