Teable 3.0

AI Spreadsheet for Business

Productivity

Spreadsheets

Artificial Intelligence

GitHub

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I am imagining a recruiting workspace with candidates, interview notes, scorecards, scheduling status, reminders, and a hiring dashboard. This seems like a natural Teable use case.

@guangyu_li “From Excels to AI operations” is a strong pitch. A lot of companies are quietly running critical processes from folders full of files, so this problem is very real.

@Jocky that's a nice loop, going from raw data straight to a working automation without switching tools. does the AI ever get the logic wrong on the first try for more conditional workflows, or is it reliably right once the relationships are set up correctly?

Congrats! @guangyu_li will give it a try

This looks useful for franchise operations. Each location could submit data through an app while the central team runs approvals, reporting, and exception handling from one source of truth.

Third launch and still shipping this hard — congrats. The "migrate any data"

part is what catches my eye; that's usually where these tools quietly fall

apart once your source data is messy.

Curious how it handles migrations where the schema doesn't map cleanly — does

it try to infer structure, or do you have to define the mapping upfront?

The mix of structured data and app generation is what caught me. Being able to turn something like receipts or customer feedback into a working workflow without moving it into another tool feels genuinely useful.

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?

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?

The thing that always sold me on Teable over the Airtable-style tools is that it's real Postgres underneath — your data stays actual SQL you can own and query, not locked in a proprietary spreadsheet blob. Curious how 3.0 handles the AI-workflow side: when an agent builds an app or automation off the data, do you get a deterministic, inspectable step you can audit, or is it prompt-driven each run? That's usually the trust gap for "AI + my business data." Congrats on the launch.

What am I missing? If I have data in a spreadsheet, using the spreadsheet as a db, why would I move the data into Teable? Maybe I am too tired but I don't understand the value prop and the problem this solves. Maybe someone can explain? Thank you!

"AI workflows" built on top of spreadsheet data is the pitch but the interesting question is what the AI layer is actually doing, like is it generating formulas, automating data entry, running analysis on the data, or orchestrating multi-step workflows that call external APIs? Those are pretty different products and the listing doesn't distinguish between them, curious which one is actually the core use case Teable users are building toward.

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.

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?

Congratulations on the launch!
natural language application building has huge potential. can multiple team members collaborate with the same AI agent simultaneously? how does collaboration work in shared workspaces?