Launching today
Timbal helps teams turn AI prototypes into production systems. Build agents and workflows, connect them to your data, design interfaces, deploy, monitor, evaluate, and govern everything from one platform. Instead of assembling separate tools for retrieval, orchestration, UI, observability, and evals, Timbal gives you one core for shipping reliable AI applications.











i like products that solve workflow issue instead of adding another tool to the stack. if Timbal can replace a few separate services that 's already a big win in my book.
Timbal AI
@georgiafor9p Georgia, that's the whole bet we're making. Every "just add one more tool" decision feels small in the moment, but a year in, most teams are maintaining a stack nobody fully understands anymore, including the people who built it.
Timbal replaces the orchestration layer, the data layer, the UI layer, and observability in one runtime. Not five vendors talking to each other through glue code, one system that already knows about all the pieces.
Timbal AI
@georgiafor9p Indeed! And this is one of the main bets we are making. Most teams end up with a vector DB, an orchestration framework, a UI tool, and an observability layer, all coming from separate vendors and having their own quirks, so it involves a lot of work to glue them together instead of building the actual product.
With Timbal, knowledge bases and retrieval run on our own hybrid DB engine instead of a separate vector DB, the UI builder is native, and observability and evaluations are part of the runtime instead of a dashboard. This means that Timbal allows you to have the four or five tools you'd normally stitch together but already in the same place and seamlessly talking to each other.
I appreciate that you're trying to simplify the AI development process without hiding the important pieces. reliability and visibility become much more valuable as projects start to grow.
Timbal AI
@sarahjadefi Really appreciate you naming that Sarah, because it's a distinction we care about a lot. Simple shouldn't mean hidden, it should mean you're not fighting the tool to see what's actually happening.
That's why everything runs with full observability and evals from day one, not something you bolt on once things start breaking. As a project scales, that visibility is usually the difference between "we caught the issue in staging" and "we found out from an angry user."
Agent 37
i find myself switching between too many AI tools during a signle project. having one platform for the whole workflow sounds much more manageable . less time configuring tools usually means more time improving the product itself.
Timbal AI
@amanda_silmon That's the exact reason this whole thing exists, Amanda!
We got tired of watching people spend more time configuring tools than actually building the thing they cared about.
Since you're here and clearly get it, we're giving away 40,000 free credits right now for anyone who wants to put Timbal through a real project. Would love to see what you'd build with it 🙌
Timbal AI
Hey PH! Pedro here, Head of Product at Timbal.
Martí covered the big picture, so I wanted to add a bit on Composer specifically, the piece I spent the most time on for this launch. Most no-code builders get you 80% of the way and then you hit a wall the moment you need real logic, a tricky auth flow, or a data model that doesn't fit the template. Composer lets you drop into actual code right at that point, no rewrite, no migration to a "real" stack later.
If you've ever hit that wall with another builder, I'd love to hear what broke it for you. That's exactly the kind of feedback that shapes what we build next.
Thanks for checking us out today 🙌
@marti_norberto I appreciate that this isn't just another agent builder. It feels like you're trying to solve the production side of AI as well. That's the part I usually end up spending the most time on.
Timbal AI
@marti_norberto @aduma__emmanuel That's the part that took us the longest to get right, and honestly the part most builders underestimate until they're already in production and things start breaking in ways they can't trace.
Getting an agent to work is the easy 10%. The other 90% is retrieval, observability, evals, permissions, all the stuff that never shows up in a demo but decides whether you can actually trust the thing with real users. That's the whole reason Timbal exists.
I've noticed that every new AI projects seems to introduce another tool into the stack. If Timble can replace even a few of those I can see value straight away.
Timbal AI
@edith__christian Edith, exactly the pattern we kept running into with our own clients before building this.
Every new AI initiative meant another subscription, another auth flow, another thing to monitor separately.
Happy to get specific if it helps. What's currently in your stack that you'd want to see replaced first? That tells us a lot about where the pain is actually concentrated.