👋 Hey Product Hunt! I'm Emir, co-founder and CEO of Sim.
Today Sim is open to everyone, and I couldn't be more excited to share it ❤️
Sim started with a mess of our own making. Waleed (my best friend and co-founder) and I were prompting Claude to build sophisticated automations in n8n, storing data in Supabase, and standing up infra for our APIs and MCPs, and we realized the stack we'd assembled just to build agents that automated our own work was a complete mess. Not to mention our token spend... So we set out to build the one platform we wished we had.
The problem: building AI agents today means stitching together frameworks, one-off scripts, and brittle automations that break the moment anything changes. We wanted one place to build an agent, give it access to our data across 1,000+ integrations, build a brain for memory, deploy it, and actually manage it over time. So we built one.
Sim is the open-source AI workspace for agents. Here's what makes it different:
🗣️ Build by chatting — describe what you want and Sim builds the agent and workflow for you. Or design it visually on a canvas. Or drop into code. Whatever fits the job.
🔌 1,000+ integrations + every major LLM — Slack, Notion, HubSpot, Salesforce, Gmail, and more, connected out of the box. Your agent says "message me on Slack when a deal closes" and it just works.
🧠 One workspace, shared context — Workflows, Tables, Knowledge Bases, and Files all live together, so your agents share memory and data instead of living in disconnected tools.
💸 Cost-efficient by design — Sim swaps token-hungry tool calls for deterministic steps and real code wherever it counts, so you're not burning tokens (and money) on work that never needed an LLM in the first place.
🚀 Built for real work — Slack bots, compliance agents, data pipelines, research assistants. Not demos, actual production agents.
🔓 Open source (Apache 2.0), SOC2, and already trusted by 100,000+ builders.
Who it's for: teams who want to put AI agents to work (IT, ops, and technical teams who need governance and control), and individual builders who care about speed and open source.
We're shipping fast and want to build this with you. Tell us what's missing, what's broken, and what would make Sim 10x more useful for you.
Try it -> sim.ai
I'll be here all day and will read and reply to every single comment 🙌
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@emirkarabeg Congratulations on the launch! "1,000 integrations" that's massive🙌🏽
love that files and tables live in the same workspace layout, context switching between three different DBs and vector tools completely breaks agent memory. amzing launch
@priya_kushwaha1 thanks so much! You can think of Sim as a 'brain' that houses and interacts with data across knowledge bases (vector DB), tables, files, and workflows.
Apache 2.0 and soc2 out of the gate is a wild combination for a new open source agent project. usually security teams block this stuff instantly. congrats for launch @emirkarabeg 🙌 qq can i run the entire stack locally via docker-compose and still keep the visual canvas working?
Thanks so much! Great question. Solo agent builders account for 70%+ of the users on the platform, while teams actually account for 90%+ of agent and workflow runs.
@emirkarabeg The mess of stitching frameworks and watching token spend go wild is incredibly relatable. Sim solving this by bringing workflows, tables, and knowledge bases into one shared context is huge for real production work.
Can we seamlessly toggle between the no-code canvas and dropping into raw code for specific nodes, or do we have to pick one style for the workflow?
@tehreem_fatima5 you can decide which option you'd like to work with and interchange for each node in your workflow.
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@emirkarabeg Being able to interchange it node-by-node gives the perfect balance between speed and full control. Absolute game-changer for dev workflows. Thanks for clarifying.
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1,000+ integrations is a lot to keep working. Are those maintained in house or community contributed?
I like that you're treating AI agents less like individual tools and more like a coordinated system. As companies adopt more agents, I think orchestration will matter far more than adding another capable model. The value shifts from what a single agent can do to how reliably they work together.
@aryan787544 exactly. Being able to orchestrate many agents to handle a single task easily will become more important over time. This concept already exists in ML, and it's called ensemble learning. Many "weak" models on average perform better than one stronger model.
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@emirkarabeg That's an interesting comparison. One difference, though, is that ensemble learning optimizes prediction quality, while companies ultimately care about decision quality. As more agents become involved, the challenge shifts from producing more outputs to determining which outputs have actually earned enough evidence to act on. That feels like the harder infrastructure problem over time
@aryan787544 I'd argue that they are more similar than different, but I agree that context is the most important aspect of the decision making process.
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@emirkarabeg That's exactly where I think the interesting question is.
Context determines which outputs become evidence, and evidence determines which agent gets trusted next. Once multiple agents start influencing each other, orchestration becomes less about execution and more about governing confidence.
I'm curious whether Sim eventually evolves more toward that layer than workflow automation itself.
Report
Love the emphasis on replacing unnecessary LLM calls with deterministic code instead of assuming everything needs an agent. Just Curious have you noticed users converging toward a small set of reusable agent patterns over time, or is every team's workflow still highly bespoke? Congrats on the launch! 🚀
A pattern we're seeing often is when teams put a set of deterministic nodes first (fetching data, cleaning it, etc.) and then put the LLM-based nodes at the end to handle the last-mile and other nuances.
Replies
Sim
@emirkarabeg Congratulations on the launch! "1,000 integrations" that's massive🙌🏽
Sim
@kutlwano_melamu thank you!
@emirkarabeg Let's go!!
love that files and tables live in the same workspace layout, context switching between three different DBs and vector tools completely breaks agent memory. amzing launch
Sim
@priya_kushwaha1 thanks so much! You can think of Sim as a 'brain' that houses and interacts with data across knowledge bases (vector DB), tables, files, and workflows.
@emirkarabeg such a good direction
Apache 2.0 and soc2 out of the gate is a wild combination for a new open source agent project. usually security teams block this stuff instantly. congrats for launch @emirkarabeg 🙌 qq can i run the entire stack locally via docker-compose and still keep the visual canvas working?
Sim
@vikramp7470 of course.
npx simstudio with docker gets you running instantly.
Triforce Todos
Congrats on the launch!
100k builders on an open source tool is genuinely impressive.
BTW, what's the split between solo devs and actual teams using this in production?
Sim
@abod_rehman
Thanks so much! Great question. Solo agent builders account for 70%+ of the users on the platform, while teams actually account for 90%+ of agent and workflow runs.
Triforce Todos
@emirkarabeg great 👍
All the best
Sim
@tehreem_fatima5 you can decide which option you'd like to work with and interchange for each node in your workflow.
1,000+ integrations is a lot to keep working. Are those maintained in house or community contributed?
Sim
@suyash_kr all maintained in house by our own agents.
who do you think gets the most value out of Sim today, developers, technical teams, or can non-technical users get productive quickly as well?
Sim
@aymi_malik
Great question.
Technical teams building agents and solo devs looking for automations get the most value out of Sim today.
Non-technical users still get loads of value from the Sim chat.
Build Check
Hey Emir! Congrats on the launch. Love open source projects and even more if it's backed by YC. Wish you all the best here
Sim
@german_merlo1 thanks so much!
I like that you're treating AI agents less like individual tools and more like a coordinated system. As companies adopt more agents, I think orchestration will matter far more than adding another capable model. The value shifts from what a single agent can do to how reliably they work together.
Sim
@aryan787544 exactly. Being able to orchestrate many agents to handle a single task easily will become more important over time. This concept already exists in ML, and it's called ensemble learning. Many "weak" models on average perform better than one stronger model.
@emirkarabeg That's an interesting comparison. One difference, though, is that ensemble learning optimizes prediction quality, while companies ultimately care about decision quality. As more agents become involved, the challenge shifts from producing more outputs to determining which outputs have actually earned enough evidence to act on. That feels like the harder infrastructure problem over time
Sim
@aryan787544 I'd argue that they are more similar than different, but I agree that context is the most important aspect of the decision making process.
@emirkarabeg That's exactly where I think the interesting question is.
Context determines which outputs become evidence, and evidence determines which agent gets trusted next. Once multiple agents start influencing each other, orchestration becomes less about execution and more about governing confidence.
I'm curious whether Sim eventually evolves more toward that layer than workflow automation itself.
Love the emphasis on replacing unnecessary LLM calls with deterministic code instead of assuming everything needs an agent. Just Curious have you noticed users converging toward a small set of reusable agent patterns over time, or is every team's workflow still highly bespoke? Congrats on the launch! 🚀
Sim
@tarqiya_forgah
A pattern we're seeing often is when teams put a set of deterministic nodes first (fetching data, cleaning it, etc.) and then put the LLM-based nodes at the end to handle the last-mile and other nuances.