I used Teable for a few months. Its a FULL PACKAGE. You can create databases, inter-connect multiple databases, fill the database fields with AI, based on one field to generate/fill another, create multiple automations, and many more.
And after all of that, create apps and websites based on those data. Agents are everywhere. They ship almost daily. I dont know how that energy come up.
Its A real piece of cake you can eat and enjoy.
Github integrations so i can push/pull/commit there and host in Cloudflare.
Design tiny things or tweaks by a few clicks instead of writing few descriptive sentences prompt.
Move databases, automations, apps from a base to another.
Allow other technologies and platforms like AstroJS, Rust/Tauri and mobile apps or desktop apps.
Support subfolder like example.com/teable-app (subdomain is already there)
Cname or something similar to change the URL of my website images from teable/amazons3/vercel CDN to my domain based URL. This is a requirement for SEO.
@thys_beesman Brandon, this is exactly the kind of complexity we built Teable for. Migration preserves the structure and flags anything that needs attention. Automations also surface issues when the underlying data changes. We’d love for you to stress test it.
@thys_beesman We usually don’t promise a “100% migration.” We aim for 200%: not merely reproducing the old Airtable system, but making it significantly more capable.
Moving rows is the easy part. The real value lives in the relationships—linked records, references, lookups, rollups, formulas, permissions, and the business logic accumulated around them. Teable’s relational model can preserve that connected structure while giving you more powerful ways to reference, query, and operate on it, all backed by real PostgreSQL.
But migration is only the starting point.
Once that relational foundation is in Teable, you can build almost any AI workflow or custom app directly on top of it. Agents can understand and act across customers, contracts, owners, approvals, renewals, and communications—not as disconnected text, but as related business context. They can generate reports, request approvals, send reminders, update records, and power purpose-built applications without forcing you to scatter logic across automation platforms, scripts, databases, and app builders.
So where exact one-to-one legacy behavior makes sense, we reproduce it. Where the old system was constrained by Airtable’s limits, Teable gives you the freedom to rebuild it better.
That’s what we mean by 200% migration: your existing relational knowledge comes with you, but the system that emerges can be far more adaptable, automated, and intelligent than the one you left behind.
Give us your hardest linked-record workflow—not the clean demo base. That’s where Teable’s relational foundation, freely customizable AI workflows, and custom apps begin to unlock possibilities that a conventional migration tool simply cannot.
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.
@alexander_shishkov1 Thank you—you’ve identified the exact trust gap we care about.
AI may help build the app or automation, but the result isn’t just a hidden prompt rerun from scratch each time. The workflow is persistent and inspectable, every execution step is logged, and individual actions can be reviewed and rolled back. You can also tightly scope what each agent is permitted to read or change.
For more complex work, multiple agents can collaborate within the same team while keeping clear responsibilities and permission boundaries.
Our principle is simple: AI can be flexible in how it reasons, but its actions on business data must remain visible, controlled, and recoverable. Real PostgreSQL provides the trusted data foundation; Teable adds the operational layer required to let agents work on it safely.
@alexander_shishkov1 Glad the Postgres foundation resonates. The workflow Teable AI creates is saved and inspectable, and each run is logged so teams can review what happened and control what the Agent can access or change.
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.
@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.
"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.
@ansari_adin Ansari, it covers them all. Teams describe the business process they need, and Teable AI works across the data, automations, integrations, and custom apps needed to make it run. A lead workflow, for example, can include importing data, enrichment, routing, follow-up emails, and a dashboard in the same workspace.
@jocky The lead workflow example is concrete enough to understand the scope, describing a process and having Teable wire together the data, automations, and dashboard in one place is a meaningful pitch for teams tired of maintaining five separate tools.
Hey, the spreadsheet-that-is-really-a-database space is crowded, so curious where you land. In my experience the moment a team spreadsheet gets important it breaks, because five people edit it and nobody trusts the numbers. Does Teable handle permissions and audit trails well enough to be the real source of truth, or is it best as a fast front end?
@artem_fedorovich That’s exactly the problem Teable is built to solve—but we’re much more than a database-spreadsheet.
Teable is a complete environment for agents to operate in. Your data, apps, automations, permissions, audit trails, and collaborators all live in one place, backed by real PostgreSQL and mature, production-grade infrastructure. Instead of critical business context being scattered across spreadsheets, automation tools, internal apps, and disconnected AI agents, Teable brings it together into one trusted system.
That means the AI doesn’t work in a vacuum. It understands the live data, permissions, and workflows your team already relies on—and can act across them seamlessly. Complex configurations and automations that once required several tools, integrations, and months of custom development can now be built and operated through one coherent experience.
Our belief is simple: teams shouldn’t have to choose between the flexibility of a spreadsheet, the reliability of a database, and the power of AI agents. Software should adapt to the way your business works, while keeping every change controlled, traceable, and trustworthy.
So yes, Teable can absolutely be your real source of truth—but that’s only the foundation. What we’re really building is the place where your data and agents work together to run the business.
I strongly recommend giving it a try with one of your real team workflows. That’s when Teable truly clicks.
@artem_fedorovich Yes, Teable is designed to be the source of truth. Permissions and audit logs stay with the same data your team uses for apps and automations, so everyone works from one trusted system.
@tehreem_fatima5 Hi Tehreem, you’re spot on. This is where Teable’s granular permissions and audit logs really earn their keep as more people start working in the same base.
One of the most interesting launches today! The Postgres-as-substrate choice is what makes the agent story believable to me. And probably most 'AI acts on your data' pitches fall apart the second an agent writes something wrong across linked records. Wondering...when an agent runs a multi-step action and step 3 fails, does the whole thing roll back as one transaction?
@artstavenka1 Great question—and this is exactly why the underlying architecture matters.
Every step is logged and traceable, individual actions can be rolled back, and agent permissions can be tightly scoped to control what each agent is allowed to read or change. If something fails mid-run, the agent can inspect the failure, attempt a fix, and continue—instead of leaving you with an unexplained, half-finished result.
And inside a team, multiple agents can collaborate across the same connected data and workflow, each with its own responsibilities and permission boundaries.
So the goal isn’t just to let AI write to your data. It’s to make agent work observable, controllable, recoverable, and collaborative enough for real business operations.
@artstavenka1 Every step is logged and traceable. If something fails along the way, the agent will inspect it, try to fix it, and do its best to finish the job.
Teable
Thank you so much—“a real piece of cake you can eat and enjoy” might be our favorite description of Teable yet!
One quick note: making small design tweaks with just a few clicks is already supported directly inside the App Preview, so you don’t need to write a new prompt for every tiny adjustment.
The GitHub workflow, moving assets between bases, broader technology support, subfolder hosting, and custom asset-domain suggestions are all thoughtful ideas. We really appreciate the detailed feedback and will seriously consider them as we continue evolving Teable. And yes—the team’s shipping energy is very real!