High-performance Rust native addon (NAPI) for cryptocurrency tax calculations with FIFO, LIFO, HIFO cost basis methods and optimized transaction processing for neural-trader accounting system

Core TypeScript library for autonomous cryptocurrency accounting with transaction management, compliance automation, fraud detection, and AgentDB-powered vector search for intelligent financial analysis

Production-ready E2B sandbox trading strategies with 10-50x performance improvements, circuit breakers, and comprehensive observability

Multi-agent swarm orchestration for autonomous accounting operations with ReasoningBank self-learning, distributed task coordination, and intelligent compliance automation for cryptocurrency trading

Investment syndicate management with Kelly Criterion allocation, voting, and performance tracking

Neural forecasting library with 27+ models (NHITS, LSTM, Transformers) for time series prediction

Comprehensive TypeScript type definitions and interfaces for neural-trader's agentic accounting system with cryptocurrency tax calculations, cost basis tracking, and capital gains reporting

Model Context Protocol (MCP) server for Claude Desktop integration, exposing intelligent accounting tools, tax calculators, and autonomous agents for AI-powered cryptocurrency financial analysis

Command-line interface for neural-trader's agentic accounting system with interactive tax calculators, transaction management, compliance reports, and cryptocurrency accounting automation

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

Self-learning market microstructure analysis with AI-powered order book prediction, swarm-based feature engineering, and real-time liquidity optimization for trading systems

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

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

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

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

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

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

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

Self-learning energy grid optimization with load forecasting, unit commitment, and swarm scheduling

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