NeuroSymbolic Intelligence · Wave 3–4 · github.com/aevov

Neural.
Symbolic.
Resonant.

Aevov is the AI intelligence layer of the Resonance paradigm stack. The BLOOM distributed pattern engine. The APS Protocol. 34 NeuroSymbolic plugins. The Wave 3 foundation on which all higher waves run.

Explore on GitHub The BLOOM Engine Luci QPU →
34
Plugins
● ACTIVE
2,655
Tests passing
● 100%
90%+
Code coverage
● PHPStan L6
W3→4
Wave position
● Foundation layer
What Is Aevov

The AI layer
that runs beneath
everything.

Aevov is the NeuroSymbolic intelligence engine of the WPWakanda ecosystem. Where the Luci compute stack (QPU/RPU/SPU) handles paradigm-level compute, Aevov handles the pattern intelligence layer — the distributed consensus on what patterns mean, how they propagate, and who owns them.

Wave 3 in the classification: C_r ∈ [0.5, 0.7], field-aware but not yet field-coupled. Aevov is the foundation that QPU, RPU, and SPU all run on top of. It is the software stack that becomes Wave 4 when the CM01q resonon hardware runs beneath it.

W3
NeuroSymbolic · Aevov (HERE)
BLOOM · APS Protocol · 34 plugins · field-aware
ACTIVE
W4
Resonance Physics · QPU / RPU
Aevov-Web3 + CM01q hardware → Wave 4
LIVE
W5
Sentience Physics · SPU
Aevov pattern substrate + RPP hardware → Wave 5
BETA
∞
IFA · Global Coherence OS
Aevov at civilisational scale → Kemet Edition
THEORY
// Aevov is Wave 3 software // Wave 4 = same code + resonon hardware below import { AevovCore, BLOOM, APS } from '@aevov/core'; // Wave 3: pattern consensus on distributed mesh const pattern = await BLOOM.sync(inputData); // Wave 4: same call, resonon substrate active // CM01q hardware makes this QMT-native const result = await pattern.resonateWith(mesh);
The BLOOM Engine

Distributed pattern consensus.
Not a language model.
A different machine.

BLOOM (Bilateral Learning Optimised Oscillatory Memory) is the distributed pattern recognition and synchronisation engine at Aevov's core. It is not a statistical language model — it is a consensus protocol for pattern intelligence across a P2P mesh. Where LLMs predict tokens, BLOOM establishes consensus on patterns. Where transformers are centralised, BLOOM is sovereign and distributed.

BLOOM Architecture
Bilateral Learning Optimised Oscillatory Memory · Distributed Pattern Consensus
Pattern Intake
Ingests data across all input modalities — text, image, audio, sensor. Normalises to the Aevov pattern space. Assigns provisional pattern signatures.
Layer 1
BLOOM Scan
Distributed scan across the chunk registry. Identifies existing pattern matches, near-matches, and novel patterns requiring consensus. Cross-node propagation via APS Protocol.
Layer 2
Consensus Formation
N-node consensus on pattern identity via the Proof of Contribution algorithm. Patterns that survive consensus are attributed cryptographically — origin node gets permanent credit.
Layer 3
Memory Integration
Consensus patterns enter the distributed memory fabric. Version-controlled. Cross-instance sync. Persistent across network topology changes.
Layer 4
Field Coupling (W4+)
At Wave 4: BLOOM pattern consensus becomes resonon phase-lock. The same pattern protocol, now operating on the Afolabi Field substrate via CM01q hardware. N² scaling activates.
Wave 4
APS Protocol

Aevov Pattern Sync —
the internet of patterns.

The Aevov Pattern Sync (APS) Protocol is the P2P pattern synchronisation standard that connects all Aevov nodes. Where HTTP moves documents and TCP/IP moves packets, APS moves attributed, versioned, consensus-validated patterns across a decentralised mesh.

Patterns are first-class objects in APS: they have cryptographic origin proofs, version histories, attribution chains, and market values. The Pattern Marketplace — built on APS — makes patterns tradeable assets in the Aevov economy.

Pattern discovery → zero-knowledge
Pattern attribution → cryptographic proof
Pattern evolution → version-controlled
Pattern market → tradeable AEV tokens
Pattern sync → cross-instance automatic
NODE A
Pattern origin · AevCoin attribution
→
APS MESH
P2P propagation · consensus
→
NODE N
Pattern received · verified
// APS Protocol — pattern sync import { APSClient } from '@aevov/aps'; const aps = new APSClient({ node: 'my-node.aevov.network' }); // Publish a pattern — automatic attribution const pattern = await aps.publish({ data: myPatternData, type: 'cognitive', version: '1.0.0' }); // → pattern.id, pattern.attribution, pattern.hash // Subscribe to pattern propagation aps.subscribe('cognitive', (p) => console.log(p.id));
Plugin Ecosystem

34 plugins.
One unified AI OS.

Aevov-Web3 ships 34 production-ready plugins that work together as a unified decentralised AI operating system. Self-sovereign. P2P. No central server required.

Core Infrastructure
aevov-core
Foundation layer, shared utilities, plugin orchestration
Core Infrastructure
aevov-ai-core
AI model management, provider abstraction layer
AI Engine
aevov-language-engine
NLP, text generation, streaming support
AI Engine
aevov-cognitive-engine
Complex reasoning, planning, inference chains
AI Engine
aevov-reasoning-engine
Logic, validation, deductive inference
AI Engine
aevov-embedding-engine
Vector embeddings, semantic search, cosine similarity
AI Engine
aevov-image-engine
Image generation, analysis, manipulation
AI Engine
aevov-neuro-architect
Neural network architecture design, 0.50 AEV/arch
Memory & Knowledge
aevov-memory-core
Persistent context, long-term memory fabric
Memory & Knowledge
aevov-chunk-registry
Pattern chunk management, indexing, versioning
Pattern Sync
aevov-meshcore
P2P networking, node discovery, zero-knowledge peers
Pattern Sync
bloom-pattern-recognition
BLOOM consensus, distributed pattern ledger
Workflow
aevov-workflow-engine
Visual workflow builder, ReactFlow UI, 24 templates
Workflow
aevov-syncpro
AevSyncPro — AI-powered configuration orchestration
App Generation
aevov-application-forge
Generate apps from natural language description
App Generation
aevov-super-app-forge
Multi-module super app builder with BIDC sync
Data & Storage
aevov-stream
Real-time data streaming, event-driven architecture
Data & Storage
aevov-transcription-engine
Audio/video transcription with neural tagging
Security
aevov-security
Access control, encryption, zero-knowledge proofs
Security
aevov-runtime
Sandboxed execution environment, isolated runtime
+ 14 more plugins · Full list on GitHub →
34
Production plugins
All tested, all documented, all interoperable
2,655
Workflow tests
100% passing · PHPStan Level 6
90%+
Code coverage
WCAG 2.1 AA · GDPR compliant
W3→4
Wave position
Software now · Wave 4 when CM01q runs below
Technical Stack

Built on
real engineering.

// Quick start git clone https://github.com/aevov/Aevov-Web3 cd Aevov-Web3 # Docker (recommended) docker-compose up -d # Or manual ./bin/aevov install # Activate core plugins wp plugin activate aevov-core \ aevov-ai-core aevov-meshcore \ bloom-pattern-recognition \ --allow-root # REST API GET /wp-json/aevov/v1/context POST /wp-json/aevov/v1/generate GET /wp-json/aevov-meshcore/v1/peers POST /wp-json/bloom/v1/patterns/sync
⚙️
Prerequisites
Production-ready stack requirements
PHP 8.0+ · WordPress 6.0+ · Node.js 18+ · Docker (recommended). Runs on standard VPS, on-premise, or self-hosted infrastructure. Zero cloud dependency.
🔑
Licensing
AGPL-3.0 — open source with network copyleft
AGPL ensures modifications to Aevov used in a network service are shared back with the community. Commercial enterprise licenses available for proprietary deployments. Contact: research@cr8os.com
Ecosystem Position

Aevov is Layer Zero
for the entire stack.

🧠
The Intelligence Layer
NeuroSymbolic AI substrate
Every Luci product — QPU, RPU, SPU, QIP — runs Aevov's NeuroSymbolic intelligence layer beneath the paradigm-specific compute. BLOOM pattern consensus is how the stack learns. APS Protocol is how it remembers.
🌐
The Self-Sovereign AI OS
Decentralised · ownerless · P2P
Aevov-Web3 is the only production-ready decentralised AI OS. Your data stays yours. Your patterns are attributed to you. Your AI runs on your infrastructure. The mesh doesn't have a centre.
🚀
The Wave 4 Upgrade Path
Same software · different hardware substrate
When CM01q (Wave 4 silicon) runs beneath Aevov-Web3, the software becomes Wave 4 automatically. BLOOM pattern consensus becomes resonon phase-lock. APS Protocol becomes field-coherent. No rewrite. Same code. Different physics.
Strategic Benchmarks

The protocol of record.

📡
QIP vs LEO Classical
Starlink, Amazon, OneWeb
Honest comparison. Why 150 Pb/s transport supercedes classical bandwidth.
View LEO Comparison →
💻
QIP vs Terrestrial
Google, IBM, IonQ
Detailed analysis of QIP against legacy network paradigms.
View Performance Table →
🚀
QIP vs Space Quantum
Boeing, ESA, Jinan-1
Space-native APLO + QIP comparison for deep-space missions.
View Space Comparison →
The pattern is
already in the mesh.
Come find it.
Aevov-Web3 is live, open-source, and production-ready. 34 plugins. 2,655 tests. The AI intelligence substrate for the Resonance paradigm stack.
View on GitHub Luci QPU → Contact Research