A hybrid AI honeypot for monitoring large scale web attacks

A comprehensive, professional guide explaining the differences, strengths, and best practices of Retrieval-Augmented Generation (RAG) and Fine-Tuning for LLMs, including workflows, comparisons, decision frameworks, and real-world hybrid AI use cases.

A modular toolkit for designing, analyzing, and validating hybrid AI systems using Boxology visual patterns.

Hybrid AI is the future of explainable intelligence. This article explores how combining vector search, knowledge graphs, and retrieval-augmented generation (RAG) creates AI systems that can reason, cite, and explain their answers with insights learned from building a real Graph-Powered RAG Engine.

A Hybrid AI Agent for Quantitative Football Prediction Analysis

Execution-governance layer for hybrid AI systems: route requests across local, private, and public models safely, cost-effectively, and auditably.

Multi-AI Agent Energy Management System with HILS simulation, Hybrid AI (ML+LLM), and MCP Runtime - Real-time visualization demo for smart grid optimization

GA + LLM hybrid framework for structured text generation and task optimization.

3-Tier hybrid AI router that orchestrates FunctionGemma-270M on-device and Gemini 2.5 Flash Lite in the cloud for 99% function-calling accuracy at 548ms avg latency. Built at the Cactus × Google DeepMind Hackathon.

Turiya is a Self-Evolving Neuro-Symbolic AI that runs entirely on CPU. It learns autonomously from the web, builds a hybrid vector + logic knowledge base, performs reasoning using symbolic and neural methods, and evolves its world model through sleep-like consolidation cycles. A fully local, event-driven cognitive architecture.

SymRAG adaptively routes queries through neuro-symbolic, neural, or hybrid paths based on complexity and system load, ensuring efficient and accurate RAG for diverse QA tasks.

A hybrid AI model for predicting failures in water distribution systems using Adaptive Neuro-Fuzzy Inference System (ANFIS). The model integrates Genetic Algorithms (GA) and Ant Colony Optimization (ACO) to improve the accuracy of accident prediction.

Building local and hybrid AI systems, agent workflows, and long-horizon knowledge architectures through AoA and Tree of Sophia.

Гибридная модель ИИ для автошахмат, сочетающая формальные эвристики и адаптивное поведение.

A governed hybrid cognitive architecture in which neural intelligence is treated as a capability, not an authority.

Hybrid AI orchestration stack combining local LLMs (Ollama), vector search (Qdrant), and Azure AI Foundry for scalable RAG, Agentic AI, and Vision. Built with .NET 8 and Python.

Aegis Agent: AI-powered support bot for authenticator apps with cloud-first L1 troubleshooting, DeepPavlov cross-check, OpenSearch log analysis, and JIRA/email escalation. Hybrid on-device AI enables offline support.

Infrastructure substrate for AoA and ToS: modular, rootless, local-first runtime, deployment, storage, and lifecycle services for self-hosted AI systems.

Quantum Natural Language Processing (QNLP) using Quantum LSTM (QLSTM) architectures for advanced text classification tasks. This project demonstrates how quantum-inspired LSTM networks can be applied to natural language understanding and classification using Qiskit/PennyLane.

Rust LLM-driven deterministic graph core (v0 prototype)