Turn your business data into AI workflows and custom apps. Connect any system, migrate any data, and build anything that fits your business 100%.
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Best
the multi-agent collaboration angle is the part that jumps out at me over the single-agent rollback question everyone else is asking. once you have two agents with overlapping permission scopes both acting on the same linked record at roughly the same time, is there any locking or conflict detection, or does it become a last-write-wins situation where the second agent's transaction just silently overwrites the first without either agent knowing a conflict happened?
@galdayan Multi-agent collaboration can’t simply mean pointing two independent agents at the same table and hoping they don’t collide.
In Teable, you can separate agents by responsibility and tightly scope what each one may read or change. Every action is logged at the step level, so overlapping writes remain attributable and inspectable, and individual actions can be rolled back if needed. Agents also work from shared, live context rather than isolated copies of the data.
We don’t want to disguise concurrency as “collaboration,” though. Permission boundaries prevent many conflicts; logs and recovery make the remaining ones visible and correctable. More explicit coordination policies for genuinely overlapping agents are an important part of making multi-agent systems trustworthy at scale.
@galdayan Gal, every step an Agent takes is recorded and traceable, while the Agent keeps working to complete the task. If two Agents touch the same data, the change history makes it clear what happened.
Report
@jocky that clears it up, thanks. one more thing - when the change history does show two agents touched the same record, does that surface as an active alert someone has to act on, or does it just sit in the log until a human happens to go looking? feels like the difference between "correctable" and "actually gets corrected" comes down to whether someone's ever prompted to check.
Interesting! Does the custom app layer support different experiences for employees, partners, and customers? That would unlock a lot of workflows currently split across portals and internal bases.
@sophialgrowth Sophia, absolutely! That’s a great use case for Teable. You can tailor the pages, actions, and data each group sees based on their role, while built-in login handles sign-in and app access. Everything runs on the same Teable data and workflows.
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this reads less like an Airtable competitor and more like someone trying to replace Retool and Airtable at the same time. that's a much bigger yet.
@kellyops Kelly, that’s a sharp read. We’re bringing the data layer, workflows, and custom apps into one place, so teams don’t have to stitch Airtable and Retool together.
Report
How does the data sync work when you're pulling from multiple sources that update at different schedules? That's always where the real complexity hides in these multi-system setups.
@talhakhalidmtk Muhammad, good question. In Teable, each source can update on its own schedule while everything flows into the same workspace. Each run is tracked, so teams can keep their data current without coordinating every source manually.
Report
used airtable for years with a pretty deep web of formulas and automations tied to slack/zapier. the pitch of 'migrate any data' sounds great until you hit the automations layer specifically - does teable actually rebuild those triggers/actions during import or just bring over the raw tables and leave you to rewire the logic by hand?
@omri_ben_shoham1 That’s a fair challenge. We don’t pretend every deeply customized Airtable + Slack + Zapier system can be imported with perfect behavioral parity in one click. Moving tables is easy; reconstructing years of automation assumptions is the hard part.
Our goal is more ambitious than creating a frozen copy. Teable preserves the relational foundation, then lets you rebuild—and often improve—those triggers and actions as freely customizable AI workflows. Instead of leaving the logic scattered across Airtable, Zapier, scripts, and Slack integrations, you can bring the data, automation, apps, and agents into one operating environment.
We like to call it a 200% migration: preserve what matters, then build something more capable than the system you left.
@omri_ben_shoham1 Once your data and relationships are in Teable, tell Teable AI how the automation should behave, and it can turn that logic into a workflow you can keep refining.
Report
building software through natural language could change how teams operate. how does Teable ensure generated applications remain easy to maintain over time? can users modify everything after AI creates it?
@james_carter35 Yes—everything remains yours to modify after the AI creates it. Natural language is the fastest way to get from an idea to a working first version, not a black box that locks you into generated output.
The app stays connected to the same relational data, permissions, and workflows underneath it, so it can evolve as the business changes. You can continue refining it with AI or edit its configuration directly. We want AI-built software to be living business infrastructure, not disposable demo code.
@james_carter35 Yes. The app remains fully editable after Teable AI creates it. You can keep refining it through natural language or make changes directly as your needs evolve.
Report
Congrats on 3.0! The Postgres foundation is what sold me. Most “AI acts on your data” tools break the second an agent touches linked records. You built on real relational structure instead. Smart bet.
One question: how do you see Teable fitting next to tools people already use? I’ve got data in Notion, Drive, and Jira. Would Teable be the source of truth those sync into, or are you asking teams to move in fully?
@tmaleh_ We don’t think adopting Teable should require replacing every tool on day one. Notion, Drive, and Jira can continue doing what they do well, while Teable becomes the connected operational layer where structured business data, workflows, apps, and agents come together.
For some teams, that gradually makes Teable the source of truth. For others, it remains the system that connects and acts across existing sources. The important part is that the agent works with real relational context instead of creating yet another isolated AI app.
And yes—please test it with a real, messy workflow. That’s where Teable makes the most sense.
@tmaleh_ You can start with one workflow and keep the tools you already use. Teable brings the data and operations for that workflow together, and can gradually become the source of truth as you move more over.
Report
Congratulation on the launch Teable 3.0 team! Really amazing stuff 🎉
Most AI-native database tools are moving toward autonomous agents. How do you see Teable balancing user control and transparency with AI-driven actions, especially when agents are modifying business-critical data at scale?
@ecopreneurphil Philip, thanks! Our approach is to give agents clear permission boundaries and keep every action visible and traceable. Teams stay in control of what agents can access and change, while agents can still carry the work through to completion.
Replies
the multi-agent collaboration angle is the part that jumps out at me over the single-agent rollback question everyone else is asking. once you have two agents with overlapping permission scopes both acting on the same linked record at roughly the same time, is there any locking or conflict detection, or does it become a last-write-wins situation where the second agent's transaction just silently overwrites the first without either agent knowing a conflict happened?
Teable
@galdayan Multi-agent collaboration can’t simply mean pointing two independent agents at the same table and hoping they don’t collide.
In Teable, you can separate agents by responsibility and tightly scope what each one may read or change. Every action is logged at the step level, so overlapping writes remain attributable and inspectable, and individual actions can be rolled back if needed. Agents also work from shared, live context rather than isolated copies of the data.
We don’t want to disguise concurrency as “collaboration,” though. Permission boundaries prevent many conflicts; logs and recovery make the remaining ones visible and correctable. More explicit coordination policies for genuinely overlapping agents are an important part of making multi-agent systems trustworthy at scale.
Teable
@galdayan Gal, every step an Agent takes is recorded and traceable, while the Agent keeps working to complete the task. If two Agents touch the same data, the change history makes it clear what happened.
@jocky that clears it up, thanks. one more thing - when the change history does show two agents touched the same record, does that surface as an active alert someone has to act on, or does it just sit in the log until a human happens to go looking? feels like the difference between "correctable" and "actually gets corrected" comes down to whether someone's ever prompted to check.
FunBlocks MindMax
Amazing product！Congrats on this launch！
Teable
@peng_wood Thank your support !!
Teable
@peng_wood Really appreciate it, Wood! We put a lot into this launch and can’t wait to hear what you think after trying it 🙌
Teable
@peng_wood Thanks, Wood! It means a lot to have your support on launch day.
Perfect for teams held together by spreadsheets and one ops hero.
Teable
@wys1010 Exactly 😂 Teable gives the spreadsheets superpowers—and finally lets the ops hero take a vacation.
Teable
@wys1010 We’ve all seen that setup 😂 Hopefully Teable can give the ops hero a little backup
Teable
@wys1010 We know that ops hero well 😄 The goal is to turn their spreadsheet setup into a system the whole team can run together.
Toki: AI Scheduling & Tasks
Teable
@sophialgrowth Sophia, absolutely! That’s a great use case for Teable. You can tailor the pages, actions, and data each group sees based on their role, while built-in login handles sign-in and app access. Everything runs on the same Teable data and workflows.
this reads less like an Airtable competitor and more like someone trying to replace Retool and Airtable at the same time. that's a much bigger yet.
Teable
@kellyops Kelly, that’s a sharp read. We’re bringing the data layer, workflows, and custom apps into one place, so teams don’t have to stitch Airtable and Retool together.
How does the data sync work when you're pulling from multiple sources that update at different schedules? That's always where the real complexity hides in these multi-system setups.
Teable
@talhakhalidmtk Muhammad, good question. In Teable, each source can update on its own schedule while everything flows into the same workspace. Each run is tracked, so teams can keep their data current without coordinating every source manually.
used airtable for years with a pretty deep web of formulas and automations tied to slack/zapier. the pitch of 'migrate any data' sounds great until you hit the automations layer specifically - does teable actually rebuild those triggers/actions during import or just bring over the raw tables and leave you to rewire the logic by hand?
Teable
@omri_ben_shoham1 That’s a fair challenge. We don’t pretend every deeply customized Airtable + Slack + Zapier system can be imported with perfect behavioral parity in one click. Moving tables is easy; reconstructing years of automation assumptions is the hard part.
Our goal is more ambitious than creating a frozen copy. Teable preserves the relational foundation, then lets you rebuild—and often improve—those triggers and actions as freely customizable AI workflows. Instead of leaving the logic scattered across Airtable, Zapier, scripts, and Slack integrations, you can bring the data, automation, apps, and agents into one operating environment.
We like to call it a 200% migration: preserve what matters, then build something more capable than the system you left.
Teable
@omri_ben_shoham1 Once your data and relationships are in Teable, tell Teable AI how the automation should behave, and it can turn that logic into a workflow you can keep refining.
building software through natural language could change how teams operate. how does Teable ensure generated applications remain easy to maintain over time? can users modify everything after AI creates it?
Teable
@james_carter35 Yes—everything remains yours to modify after the AI creates it. Natural language is the fastest way to get from an idea to a working first version, not a black box that locks you into generated output.
The app stays connected to the same relational data, permissions, and workflows underneath it, so it can evolve as the business changes. You can continue refining it with AI or edit its configuration directly. We want AI-built software to be living business infrastructure, not disposable demo code.
Teable
@james_carter35 Yes. The app remains fully editable after Teable AI creates it. You can keep refining it through natural language or make changes directly as your needs evolve.
Congrats on 3.0! The Postgres foundation is what sold me. Most “AI acts on your data” tools break the second an agent touches linked records. You built on real relational structure instead. Smart bet.
One question: how do you see Teable fitting next to tools people already use? I’ve got data in Notion, Drive, and Jira. Would Teable be the source of truth those sync into, or are you asking teams to move in fully?
Either way, I want to try it on a real workflow.
Teable
@tmaleh_ We don’t think adopting Teable should require replacing every tool on day one. Notion, Drive, and Jira can continue doing what they do well, while Teable becomes the connected operational layer where structured business data, workflows, apps, and agents come together.
For some teams, that gradually makes Teable the source of truth. For others, it remains the system that connects and acts across existing sources. The important part is that the agent works with real relational context instead of creating yet another isolated AI app.
And yes—please test it with a real, messy workflow. That’s where Teable makes the most sense.
Teable
@tmaleh_ You can start with one workflow and keep the tools you already use. Teable brings the data and operations for that workflow together, and can gradually become the source of truth as you move more over.
Congratulation on the launch Teable 3.0 team! Really amazing stuff 🎉
Most AI-native database tools are moving toward autonomous agents. How do you see Teable balancing user control and transparency with AI-driven actions, especially when agents are modifying business-critical data at scale?
Teable
@ecopreneurphil Philip, thanks! Our approach is to give agents clear permission boundaries and keep every action visible and traceable. Teams stay in control of what agents can access and change, while agents can still carry the work through to completion.