CopilotKit
CopilotKit is a full-stack framework for building user-interactive AI agents and copilots that live inside applications, enabling context-aware experiences beyond traditional chatbots.
At a Glance
- Software Developers
- AI Engineers
- Enterprise SaaS
- Fortune 500 Companies
AI Tools by CopilotKit
(2)
Channels SDK
AI Agent Messaging Platform SDK
CopilotKit
React SDK for Agentic AI Apps
Discussions
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Latest News
OpenBox AI Partners with CopilotKit to Bring Enterprise-Grade Trust to Agentic AI
CopilotKit Raises $27 Million to Help Developers Build App-Native AI Agents
CopilotKit Raises $27M Series A to Build Infrastructure for AI Agents
CopilotKit Closes $6.5M Seed Round
Products & Services
An open-source (MIT) full-stack framework for building AI copilots and agents within web applications.
The 'Agent-Graphic User Interface' protocol that standardizes how AI agents communicate with and manipulate application interfaces.
SDK for building multi-channel agentic experiences.
A persistence and infrastructure layer for enterprise-grade AI agents, supporting self-hosting and VPC deployments.
Market Position
Horizontal AI agent infrastructure focused on the 'Agentic Frontend' and standardizing AI-UI communication via the open AG-UI protocol, differentiating from vertically integrated or chatbot-only solutions.
Leadership
Founders
Atai Barkai
Co-Founder & CEO. Physics background from University of Pennsylvania (BS/MS). Experienced in building large-scale developer infrastructure.
Uli Barkai
Co-Founder & CMO/Head of Growth. Studied Financial Economics at Columbia and Philosophy at Tel Aviv University. Co-organizer of AI Tinkerers San Francisco.
Executive Team
Atai Barkai
Co-Founder & CEO
Physics degrees from UPenn; infrastructure engineering background.
Uli Barkai
Co-Founder & Head of Growth/Partnerships
Financial economics and philosophy background; AI ecosystem leader.
Board of Directors
Founding Story
Founded by brothers Atai and Uli Barkai, CopilotKit was started with the vision that the 'chatbot in a sidebar' approach is inefficient. They aimed to create 'agentic interfaces' where AI agents can directly interact with app UIs, understand user context, and generate interactive components.
Business Model
Revenue Model
Open-core model with cloud hosting, tiered subscriptions for pro/team features, and enterprise licenses for self-hosting/VPC deployments.
Pricing Tiers
1 seat, 200 threads, 3-day retention.
Up to 5 seats, 5,000 threads, 5-day retention.
5 seats included, 25,000 threads, 14-day retention, dedicated support.
Unlimited threads, custom retention, SLA, and engineering support.
Target Markets
- Software Developers
- AI Engineers
- Enterprise SaaS
- Fortune 500 Companies
- Building app-native AI assistants
- Creating interactive agentic dashboards
- Automating complex multi-step workflows within SaaS applications
- Enhancing user engagement with context-aware AI
- Cisco
- DocuSign
- Deutsche Telekom
- S&P Global