RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs

Universal memory layer for AI Agents

Build, deploy, and orchestrate AI agents. Sim is the central intelligence layer for your AI workforce.

This repository delivers end-to-end, code-first tutorials covering every layer of production-grade GenAI agents, guiding you from spark to scale with proven patterns and reusable blueprints for real-world launches.

The conversational control layer for customer-facing AI agents - Parlant is a context-engineering framework optimized for controlling customer interactions.

Open-source text-to-SQL and text-to-chart GenBI agent with a semantic layer. Ask your database questions in natural language — get accurate SQL, charts, and BI insights. Supports 12+ data sources (PostgreSQL, BigQuery, Snowflake, etc.) and any LLM (OpenAI, Claude, Gemini, Ollama).

Memory layer for AI Agents. Replace complex RAG pipelines with a serverless, single-file memory layer. Give your agents instant retrieval and long-term memory.

Memori is agent-native memory infrastructure. A SQL-native, LLM-agnostic layer that turns agent execution and conversation into structured, persistent state for production systems.

The live data layer for apps and AI agents. Create up-to-the-second views into your business, just using SQL

Open-source context retrieval layer for AI agents

Orchestration layer for coding agents (Claude Code, Codex)

Universal memory layer for AI Agents. It provides scalable, extensible, and interoperable memory storage and retrieval to streamline AI agent state management for next-generation autonomous systems.

ByteRover CLI (brv) - The portable memory layer for autonomous coding agents (formerly Cipher)

Real-time transport layer for Java AI agents. Build once with @Agent — deliver over WebSocket, SSE, gRPC, MCP, A2A, AG-UI, or any transport. Works with Spring AI, LangChain4j, Google ADK, Embabel, Koog or the built-in OpenAI-compatible client.

Agent Skills as a Memory Layer

The Open Source Memory Layer For Autonomous Agents

Asynchronous coordination layer for AI coding agents: identities, inboxes, searchable threads, and advisory file leases over FastMCP + Git + SQLite

Self-learning data agent that grounds its answers in 6 layers of context. Inspired by OpenAI's in-house implementation.

GoClaw - GoClaw is OpenClaw rebuilt in Go — with multi-tenant isolation, 5-layer security, and native concurrency. Deploy AI agent teams at scale without compromising on safety.

7/24 Office — Self-evolving AI Agent system. 26 tools, 3500 lines pure Python, MCP/Skill plugins, three-layer memory, self-repair, 24/7 production.

The open source post-building layer for agents. Our environment data and evals power agent post-training (RL, SFT) and monitoring.

FinMem: A Performance-Enhanced LLM Trading Agent with Layered Memory and Character Design

:brain: 100% Local Memory layer and Knowledge base for agents with WebUI

Core 7 layers of production grade agentic system

Your AI agent in 30 seconds. Not 30 hours. Self-hosted, open-source personal AI with desktop installer, multi-agent Command Center(Deep Work), and 7-layer security. Anthropic, OpenAI, or Ollama.

Single-file memory layer for AI agents, sub mili-second RAG on Apple Silicon. Metal Optimized On-Device. No Server. No API. One File. Pure Swift

The open-source state layer for AI coding agents. Turn chaotic agent sessions into structured, traceable workflows with a local workspace for runs, events, and collections.

"AnyTool: Universal Tool-Use Layer for AI Agents"

Supercharge Claude Code with 11 AI agents, 36 commands & 15 skills — the claude-code plugin framework inspired by oh-my-zsh. 6-layer security hooks included. 5-min install.

The LLM abstraction layer for modern AI agent applications.