We started Agentplace as a builder for AI websites.
Now we're building something bigger. Agentplace lets you create specialized AI agents for real tasks and workflows, like AI teammates that help you get work done.
Build, test, and deploy agents fast, and improve them as you go.
This is the 3rd launch from Agentplace. View more
Agentplace AI Agents
Launched this week
Start with ready agents for common workflows or create your own in minutes.
Agentplace lets you build specialized agents for tasks like lead routing, research, document analysis, scheduling, and internal support. Use them yourself, share them with your team, or connect them to the tools you already use.
Agentplace handles the infrastructure so you can focus on the workflow.
Free Options
Launch Team / Built With
Congrats on the launch! What happens when a model gets updated or replaced? How much work is it to re-test and adjust an existing agent?
@ermakovich_sergey Thanks! Good question. On our side, we have internal benchmarks for the Builder agent, so when a new model drops we can test and adapt pretty quickly, usually a day or two. As for the agents users have already built, we don't remove access to older models, so everything keeps working as before. If a user wants to switch to a newer model, we'd recommend testing it on their end to make sure things behave as expected. But nothing breaks automatically.
Agentplace
@ermakovich_sergey, adding to Boris's comment, you can connect any eval tool to enable a controlled change.
Agentplace
@ermakovich_sergey Thank you for support us!
Huddle01 Cloud
Interesting that this is built around workflows and not just 'we have AI now.' Quick question: how easy is it for an ops person to pick this up without looping in engineering every time? That's usually where these things break down.
Agentplace
@shalini_umrao Thank you for bringing this up. That's actually who we built this for. The whole point is that an ops person can build and update agents on their own. There's no code to write, you describe what you want the agent to do in plain text, test it in the same window, and hit publish. If something needs fixing you just open the editor, change the prompt, test, publish again. No pull requests, no deploys, no waiting for engineering
Agentplace
@shalini_umrao Exactly. If every small change needs engineering, adoption usually stalls.
Can Agentplace plug into existing pipelines without restructuring, or do teams inevitably have to adapt their stack?
Agentplace
@athsara Agentplace can plug in natively, so no need to adapt. That being said, AI is a different animal, and we found that to use it to its full power, the process should be different and in many cases simplified.
Agentplace
@athsara Each agent is also an MCP server so you can just make a small one that does one thing and plug it into what you already have. Or if MCP doesn't fit you can add custom API endpoints since it's a full Node.js app under the hood. Either way you don't need to rebuild anything
How do you handle reliability and trust when agents become more autonomous like specifically, what mechanisms exist for debugging, auditing decisions, and preventing silent failures in production workflows
Agentplace
@lak7 Honestly this is an area we're still working on. Right now each agent runs in an isolated VM and you have SSH access from the builder so you can check what's happening. For published agents we don't have built-in logging or audit yet. Since you have full access to the source code though, it's pretty easy to plug in something like Langfuse or Sentry or whatever monitoring you already use. So right now this is more on the user side, but built-in observability is on our list.
@evgeny_sorokin Gotcha! I am using agentplace but it would be cool if there is an docs for its usage. Specifically to edit agent
Agentplace
@evgeny_sorokin @lak7 Awesome! Thank you for trying Agentplace!
Agentplace
@evgeny_sorokin @lak7 we definitely need to make it happen
@lak7 That’s exactly why transparency matters so much to us. If agents are doing real work, people need a clear way to inspect actions, audit decisions, and catch failures early.
Neurcode AI
Seems interesting.
How reliable is it though? If given full access of system?
Agentplace
@sujit_jaunjal Could you tell more about what you mean by full access of system? Depending on what you have in mind the answer might be different. But from our side, each agent runs in its own isolated VM, you have SSH access right from the builder so you can check what's going on inside anytime, and if you ever want to move away you can sync the full source code to GitHub. So it's not a black box situation.
Agentplace
@sujit_jaunjal Totally if an agent gets real access - it shouldn’t feel like a black box.
Agentplace
@sujit_jaunjal, in short, it is reliable
@sujit_jaunjal Exactly why we think visibility matters so much. If an agent has deep access, reliability has to come with transparency and control.
Rectify
This looks genuinely useful. Can you build something really specific for one role, like recruiting or sales ops?
Agentplace
@umar_lateef Yes, absolutely, that’s actually one of the main ideas. You can build something very specific for a role like recruiting or sales ops.
Agentplace
@umar_lateef yes, and it works best if you tune it to a specific role, it is still not AGI though :)
@umar_lateef Definitely that’s a big part of what we’re building for. It can be very tailored to a specific role, whether that’s recruiting, sales ops, or something else entirely.
The timing for this is perfect. I've been looking for a way to automate our lead routing without having to dive into complex code. Agentplace looks like it hits the sweet spot between simplicity and power. Huge congrats on the 3rd launch! Just curious, does it support custom API integrations for CRM tools yet?
Agentplace
@heyethan54 Appreciate it, that’s exactly the kind of use case we’re seeing a lot.
And yes, you can connect custom APIs. We support integrations through tools and can wire agents into CRM workflows.
Happy to share a quick example if helpful.
@heyethan54 Thanks, yep, that’s very much where we’re heading: connecting agents to external tools and workflows, and CRM is one of the clearest use cases.