rUv

High-performance neural network swarm orchestration in WebAssembly

DSPy.ts 2.1 - 100% DSPy Python compliant TypeScript framework with multi-agent orchestration, self-learning capabilities, MIPROv2 optimizer, and comprehensive module library. Powered by AgentDB, ReasoningBank, and Swarm architecture.

SPARC 2.0 - Autonomous Vector Coding Agent + MCP. SPARC 2.0, vectorized AI code analysis, is an intelligent coding agent framework built to automate and streamline software development. It combines secure execution environments, and version control into a

N-API bindings for QuDAG quantum-resistant DAG and cryptography

AI Defense System - Production-ready security middleware for protecting AI applications from prompt injection, manipulation attacks, and adversarial inputs. Available as both 'aidefence' (British) and 'aidefense' (American).

High-performance WebAssembly theorem prover with dependent types, hash-consing (150x faster), Ed25519 proof signatures, MCP support for Claude Code, AgentDB vector search, episodic memory, and ReasoningBank learning. Formal verification with cryptographic

Dual-protocol payment infrastructure for autonomous AI commerce (AP2 + ACP)

WebAssembly-powered temporal analysis toolkit - DTW, LCS, scheduling, and meta-learning

Unified TypeScript API surface for RuVector WASM - attention, learning, economy, and exotic features

Ultra-low latency neural trading engine with Rust + Node.js bindings

⚡ Ultra-fast neural network inference in WebAssembly - sub-microsecond latency

Blazing fast graph pathfinding SDK powered by WebAssembly. 10-15x faster than JavaScript implementations.

V3 Embedding Service - OpenAI, Transformers.js, and Mock providers

Memory module - AgentDB unification, HNSW indexing, vector search, hybrid SQLite+AgentDB backend (ADR-009)

Integration module - agentic-flow@alpha deep integration, ADR-001 compliance

Self-learning LLM runtime — TurboQuant KV-cache (6-8x compression), SONA adaptive learning, FlashAttention, speculative decoding, GGUF inference

Multi-LLM Provider System for Claude Flow V3

Shared module - common types, events, utilities, core interfaces

Healthcare optimization with self-learning patient forecasting and swarm-based staff scheduling

Neuromorphic computing with Spiking Neural Networks, STDP learning, and reservoir computing for ultra-low-power ML

Self-learning dynamic pricing with RL optimization and swarm strategy exploration

Self-learning vehicle routing optimization with multi-agent swarm coordination

Self-learning evolutionary game theory with multi-agent tournaments, replicator dynamics, and ESS calculation

Adaptive burst scaling system for ruvector - handles 10-50x traffic spikes

Command-line interface for RuVector vector database with self-learning hooks

NPX package to scaffold new projects with SPARC methodology structure

Quantum-inspired optimization algorithms with swarm-based circuit exploration for combinatorial and constraint problems

Self-learning demand forecasting and swarm-based inventory optimization with uncertainty quantification

Self-learning portfolio optimization with benchmark swarms and multi-objective optimization

Self-learning energy forecasting with conformal prediction and swarm-based ensemble models

Standalone swarm coordination - up to 100+ agents, 4 topologies, hive-mind, consensus

WASM bindings for Neural Trader — market events, coherence gates, replay memory

Performance module - benchmarking, Flash Attention validation, optimization

Command-line interface for QuDAG quantum-resistant DAG operations

Open source Claude Code CLI — based on ruDevolution decompilation of v2.1.91

Security module - CVE fixes, input validation, path security

Testing module - TDD London School framework, test utilities, fixtures, and mock services for V3 Claude-Flow