Build custom business apps such as internal tools or client portals incredibly fast and without code. Use drag-and-drop UI components to assemble complex multi-page apps on top of any data source.
This is the 3rd launch from Jet Admin. View more
Jet AI Agents
Launching today
Jet AI Agents is the AI builder that lets teams create business apps and AI agents on top of 200+ tools — without code. Work with agents like teammates directly in Slack, WhatsApp, or Telegram.
Marketing, sales, operations, and support teams use Jet to build AI agents, AI workflows, and apps that don’t just display data — they take action.
Teams use Jet to automate the workflows that matter most.
AI agents your team will trust — because they built them themselves.
Free Options
Launch Team / Built With
Jet Admin
Hey everyone 👋
We built Jet AI Agents because most teams still:
- jump between tools
- manually run workflows
- rely on engineering for simple internal tools
So we asked:
👉 what if business teams could build their own AI agents — on top of real data — and actually automate work?
With Jet, you can:
- build ai agents without code
- enrich AI with your data & 200+ integrations
- let them answer questions and take action in Slack, Telegram, WhatsApp and more
- instantly generate visual reports
- self-host in your own environment
- use open-source AI models
- bring your knowledge into AI — from files, drives, websites, and multiple formats like DOCX, PDF, JSON, MP3.
We’ve also created a few templates to help you get started (the real magic is in customizing them ✨):
📊 Data Analysis Agent 👉 https://www.jetadmin.io/agent-templates/bigquery-data-analyst
🗓️ Meeting Preparation Agent 👉 https://www.jetadmin.io/agent-templates/meeting-prep-agent
🎧 Support Agent 👉 https://www.jetadmin.io/agent-templates/customer-support-agent
📝 Meeting Analysts Agent 👉 https://www.jetadmin.io/agent-templates/meeting-notes-agent
Would love your feedback:
👉 What’s the first workflow you’d automate?
interesting take on bundling workflows + agents under one platform. one thing i'd be curious about — when you have agents calling into the same data layer simultaneously, how do you handle scope conflicts? in my own setup (claude code on a nuxt 3 + go-zero stack) i ended up writing per-folder AGENTS.md files just so concurrent sub-agents wouldn't step on each other.
does jet handle that internally or is it more about the orchestration layer? curious about the design choice.
Jet Admin
@ethanfrostlove thanks for question! for cases when you need fixed flow or data segments applied - we suggest adding exact Workflows to Agent instead of adding full resource/collection, in Workflows you can apply any filters, sorting, etc. depending on Agent or other conditions using our no-code or AI workflow builder
The 'relying on engineering for simple internal tools' line is the story of my life. My backlog is 6 months deep with 'just one more internal dashboard' requests. If Jet lets my business ops team build their own BigQuery analyst without touching a line of code, you’ve just saved me 20 hours a week. Does it handle write-back permissions safely?
@anton_svetlov
Jet Admin
@priya_kushwaha1 thanks for question! sure, you can either specify agents read/write/delete operations granularly per each collection or even create exactly workflows with applied filtering, sorting, etc. which agents can use
"AI agents your team will trust - because they built them themselves" hits different. we've had mixed results with off-the-shelf AI tools in healthcare workflows, but letting domain experts build their own makes sense. what's the learning curve like for non-technical users?
Jet Admin
@piotr_pasierbek thanks, and you nailed it on generic AI tools in regulated workflows.
The learning curve is surprisingly gentle: most non-technical folks ship their first agent in 5-10 minutes, especially when starting from a template. It's a visual builder (no code), and you can ground the agent in your own SOPs and PDFs so it speaks your domain from day one.
Would love to hear what use case you'd tackle first! 👀
the Slack integration is smart - we've been looking for something that lets our team build agents without pulling devs away from core product work. curious how the 200+ tool connections handle auth and permissions? does each team member need to connect their own accounts or can you set up shared service accounts?