Memora

Byzantine-safe shared state for federated learning and agent swarms

Memora is a state layer for federated learning, multi-agent systems, and edge swarms that aims to keep shared data byte-identical across heterogeneous nodes. It focuses on signed writes, deterministic aggregation, and Byzantine-robust consensus rather than general-purpose agent execution.

Agenticness = how independently a tool can take action, scored across 9 dimensions. Scored independently by David Kooi, Skylark Creations — see full rubric →

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Self-Hosted

On-Device / Edge

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About

What It Is

Memora is a distributed state and consensus layer built for federated learning, multi-agent systems, and edge or defence swarms. According to the site, it replaces floating-point aggregation with fixed-point Q16.16 arithmetic so updates stay deterministic across ARM, x86, and GPU hardware.

What to Know

Memora’s main strength is its focus on integrity and determinism in shared state, especially where heterogeneous hardware or adversarial participants can cause silent forks. The documentation emphasizes signed writes, attribution, Byzantine-robust...

Key Features

Fixed-point Q16.16 aggregation for deterministic cross-hardware results

Byzantine-fault-tolerant state layer for federated learning and edge swarms

Signed and attributable writes

OR-Set CRDT delta-state storage

Drift detection and human-in-the-loop escalation

Use Cases

Federated learning systems that need deterministic model update aggregation across heterogeneous hardware

Multi-agent applications that share memory and need protection against poisoned or conflicting writes

Edge or drone swarms that must keep synchronized state under partition or adversarial conditions

Agenticness: Guided Assistant

Executes tasks you assign, one step at a time, within narrow domains.

High evidence

Last evaluated: Aug 3, 2026

Dimension Breakdown

Action Capability

Autonomy

Planning

Adaptation

State & Memory

Reliability

Interoperability

Safety

Operator Sovereignty

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