Hybro AI
Hybro AI is building an open interoperability layer for AI agents: a hybrid platform that lets local/on-device and remote/cloud agents discover, communicate, collaborate, and execute multi-agent workflows. It emphasizes human control, privacy, and the open Agent2Agent (A2A) standard.
At a Glance
- AI-agent developers and engineering teams
- Organizations deploying multi-agent workflows
- Privacy-sensitive teams needing local execution
- Enterprises and cross-organization agent networks
- +1 more
AI Tools by Hybro AI
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Hybro
Open Source A2A Agent Hub
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Latest News
A2A Adapter v0.2.16 released with correctness fixes across executor/subprocess/CLI, restart-safe sessions, safer n8n webhooks, OpenClaw support, and hardened LangGraph/LangChain/CrewAI/Callable adapters.
Hybro v0.4.4 released; latest patch release in the new 0.4 single-image distribution line.
Hybro v0.4.0 released with single-image install, browser model-provider setup, bundled agents, embedded MongoDB, MCP/API access, and POSIX shell/npm CLI.
A2A Adapter v0.2.15 released with stdin-based Claude Code prompts and a CLI skill option/default Agent Card skill.
Products & Services
Open-source hybrid multi-agent interoperability platform with an async FastAPI backend and Next.js dashboard. It provides agent discovery, execution rooms, orchestration, real-time streaming/inspection, human approvals, network topology, HTTP API, and MCP access; it can run locally in a single container.
Apache-2.0 Python SDK and CLI that wraps agent CLIs, frameworks, workflow engines, and custom Python agents as A2A servers. It handles AgentCard generation, JSON-RPC, task lifecycle, and streaming.
Lightweight local daemon/Python package that connects local agents to hosted hybro.ai over outbound HTTPS, allowing local/private agents and cloud agents to appear together in one portal.
FastAPI/Next.js tool for validating and inspecting A2A communication, compliance, agent capabilities, and real-time interactions; deployable with Docker.
Market Position
Hybro positions itself as an open, hybrid interoperability layer rather than a single-agent application or framework-specific orchestrator. Its differentiators are local-plus-cloud execution, privacy-preserving connectivity, A2A-native routing, human approvals, and a unified network/dashboard; the competitive set includes framework/orchestration tools such as LangGraph, CrewAI, LangChain, n8n, and cloud-centric agent platforms, which Hybro also integrates with or connects to.
Leadership
Founders
Kevin Lu
Founder and CEO; a seasoned engineer and serial entrepreneur with about a decade of experience building large-scale infrastructure systems, and described publicly as ex-Google.
Jerome Cai
Co-founder/technical builder; described by Hybro's F6S profile as a passionate hacker, full technical builder, and fast shipper. He is also a principal contributor to Hybro's open-source repositories.
Executive Team
Kevin Lu
Co-founder and CEO
Seasoned engineer and serial entrepreneur with about a decade of large-scale infrastructure experience; publicly described as ex-Google.
Jerome Cai
Co-founder / technical builder
Passionate hacker and full technical builder; a major contributor to Hybro, A2A Adapter, and related open-source repositories.
Founding Story
Hybro says AI agents were proliferating but operating in silos: for example, an agent from one organization could not collaborate with an agent from another. The founders created Hybro to provide an open, cross-organization network and hybrid interoperability layer so local and remote agents can work together while people retain control.
Business Model
Revenue Model
The core Hybro, A2A Adapter, Hub, and Inspector software is open source. Hybro also operates a hosted hybro.ai network/service to which local agents can connect through Hybro Hub and API keys; public pricing or revenue figures were not found.
Target Markets
- AI-agent developers and engineering teams
- Organizations deploying multi-agent workflows
- Privacy-sensitive teams needing local execution
- Enterprises and cross-organization agent networks
- Open-source AI infrastructure users
- Multi-agent research, planning, and workflow execution
- Connecting coding agents and harnesses such as Claude Code and Codex
- Local/private AI agents collaborating with specialized cloud agents
- Enterprise and cross-organization agent interoperability
- Human-reviewed document, legal, finance, support, travel, and operations workflows
- Developing, exposing, testing, and inspecting A2A-compatible agents