C1 by Thesys is a Generative UI API that augments LLMs to respond with interactive UI like charts, forms, cards, and more in real-time, instead of plain text. It integrates seamlessly with any LLM, framework, or MCP in just 2 lines of code. Ship rich, interactive AI apps 10x faster with 80% less UI overhead.
This is the 4th launch from Thesys. View more
Agent Builder by Thesys
Launched this week
Build AI agents that reason dynamically and respond with charts, cards, forms, slides and reports. No workflows. No code. Just connect your data, add instructions, customize style, and publish and share with anyone or embed on your site.
Free Options
Launch Team
Thesys
Hey folks, Parikshit here, co-founder of Thesys. 👋
Today, we’re launching Agent Builder 🚀
A no-code agent builder to create truly agentic AI apps that respond with interactive UI like charts, forms, cards, slides, and reports, not plain text.
No code. No workflows. No frontend work.
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⛔️The problem:
Modern AI agents aren’t workflow scripts anymore.
They reason, adapt, and decide. Tools like Claude Co-Work show this clearly.
But most agents are still text-in, text-out.
They answer questions, then stop.
Users still interpret results, build slides, create reports, or take action.
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❇️ The solution:
Thesys Agent Builder lets you create fully functional AI agents in minutes.
You define intent and guardrails.
The agent decides how to respond and what interface to generate.
They can return:
📊 Charts and dashboards from your data
📝 Forms users can fill and submit
🧩 Cards, tables, and interactive components
📑 Slides and reports ready to share
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🛄 The steps:
Get started in 3 steps. No code.:
1️⃣ Connect your data
Files, URLs, databases, or tools via MCP
2️⃣ Customize your agent
Add instructions. Set tone, style, and behavior.
3️⃣ Test and Share it
Publish with a link or embed it on your website.
Your agent goes live instantly.
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✳️ The possibilities:
What you can build :
📈 Analytics agents for visual insights
🤝 Website copilots for guidance and support
💰 Sales agents that improve conversions
🛒 Ecommerce copilots for discovery and comparison
All without writing code or managing UI.
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Under the hood, Agent Builder is powered by C1, our Generative UI engine that handles UI generation, orchestration, and runtime, so AI apps actually help users get work done.
🎁 Launch bonus: Free credits to build your first agent
👉 https://www.thesys.dev/agent-builder
Would love your feedback.
Excited to see what you build 🙌
This is what Claude Artifact Builder should have been but apparently they abandoned the project. Glad to see someone pushing this!
Thesys
@phuctm97 Do give it a try and let us know if you have any suggestions!
The "respond with UI instead of text" approach is exactly what conversational AI needs. I'm curious about how UI state is managed during multi-turn conversations - when a user modifies a previously generated chart or form, does C1 perform incremental updates on the existing component or regenerate from scratch? Also, is there support for preserving partial UI state when the conversation context shifts?
Thesys
@yamamoto7 we generate new charts in conversations however we are moving towards live charts where the data can be refreshed.
Can you elaborate what you mean by partial UI state?
Roster
so useful
Thesys
@mark_vu Thanks Mark. What use cases do you have in mind?
Migma AI
AI agents responding with actual UI instead of text walls?? this is the future fr
Thesys
@adam_lab yep. we did a user research for AI chatbots and found 83% users preferred Generative UI.
Please check it out!
|https://www.thesys.dev/report/gen-ui-2025
Interactive UI is a big leap. How do you ensure consistency so the same intent doesn’t produce wildly different interfaces across runs?
Thesys
@shreya_chaurasia19 you can add system prompts to guide generations and ensure consistency across runs
Product Hunt
Thesys
@curiouskitty We initially started as a developer-focused tool. However, through conversations with users, we quickly realized that non-developers also wanted a simple way to iterate, connect their tools, and experiment with interactions without needing deep technical expertise.
Based on this feedback, we built and shipped features that made it easier for a broader range of users to get started and see value quickly.
We’re also working on adding support for exporting and deploying on users’ own infrastructure. This will give teams greater flexibility, control, and customization to fit their specific needs.