Been using splox for 2 months as a person with a very limited coding background - it opens up a lot of opportunities. Much cheaper and easier to operate than known vibe coding solutions.
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Maker
📌
Hey Product Hunt!
I’m Boris Mucha, a full-stack + ML developer. In the past, I worked a lot on developing scalable systems, including for AI pipelines. For the last 1.5 years I’ve been pouring my days and nights into Splox, because I believe AI shouldn’t work alone. Real problems need agents that can collaborate and scale — and I love building toward that future.
What started as a solo grind is now being used by early companies and over 27 testers running real multi-agent systems. One of them has 2M+ MAU — so Splox is already battle-tested at scale. I’m excited to finally launch Splox here on Product Hunt. At one stage, agents were handling about 90% of Splox’s workflows and development tasks — while I focused mainly on reviewing and tackling deeply complex parts that still require human expertise.
What you can build with Splox:
Autonomous Dev Team — all the way to full deployment on your server.
Customer support agents that handle routine tickets and escalate only when needed.
Proactive social agents — they initiate conversations, follow up, and can message you on Telegram (or other channels) or call you on your mobile.
Creative Agents — from one query, generate short-form videos, comics, or other media (script → visuals → voice → export).
Adaptive Cybersecurity Mesh — agents that develop new threat detection methods, create custom security tools for novel attacks, and continuously evolve their defense strategies by sharing intelligence with each other.
Autonomous Scientific Discovery Network — agents that formulate new hypotheses, design their own experiments, create custom analysis tools, and fundamentally change their research approaches based on discoveries.
If you’re curious about the tech side, here’s what Splox does:
Multi-agent platform — agents collaborate in parallel or sync when needed
Flexible connections — actor, orchestrator, or fully custom patterns
Sandbox environments — agents can run their own isolated sandboxes (including local MCP). They don’t just use tools, they can build and reuse them
3000+ connectors (including local mcp) — many pre-configured (LLM, image, video, TTS etc.), ready out of the box. Add your own keys anytime for advanced use
RL on top of LLMs — support for advanced adaptive agents
Agent-to-agent scheduling — agents can proactively assign and trigger each other’s tasks, enabling proactive coordination
Pricing — no subscriptions, just commission-based: pay only when your agents work
Simple examples:
MetaAgent — an agent that builds trading system by combining agents like Trader, Social Monitor, and Researcher → https://youtu.be/XcYU4bLT8TA
Splox is in whitelist-only beta. Try it in 2 minutes: spin up your first agent from a template at https://beta.splox.io/templates.
Thanks for checking it out 🙏 I’ll be here in the comments all day, answering questions and sharing more about the journey.
If you had Splox today, what’s the first system you’d try building?
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🤯 Built a full MVP in 4 hours instead of a month using Splox
Hey hunters! Just had to share this insane experience with Splox.
The setup: I needed to build an MVP for a client project. Usually, this would mean assembling a team, planning sprints, and delivering in 4-6 weeks.
What actually happened: I used @Splox with help of @goreactdev to build a custom multi-agent flow.
Than we set up MVP with just two prompts:
Build a working prototype based on my design specs with these features...
Add OAuth authentication and connect it to a database
That's it. The multi-agent system we created literally built the entire thing while I watched.
The agents worked like a real dev team:
Frontend Agent built React components with proper state management
Backend Agent set up APIs, database schemas, and auth flows
QA Agent found bugs I would've missed
DevOps Agent deployed everything to production
They all shared context and coordinated perfectly
They asked me clarifying questions via Telegram when needed and kept building. Frontend waited for Backend's APIs. QA tested in parallel. Like watching a senior team that's worked together for years.
What blew my mind: These agents don't just execute tasks — they actually collaborate. When the Backend agent changed an API endpoint, Frontend automatically adapted. When QA found an issue, the responsible agent fixed it without me intervening. They even suggested architectural improvements I hadn't considered.
Real talk: This isn't "no-code" or "low-code" — it's actual production-ready code written by AI agents working together. I only stepped in for critical architecture decisions.
We're living in the future where one person with the right tools can ship what used to take entire teams. Boris and the Splox team just made that future accessible.
The multi-agent flow we built together is now my go-to for rapid prototyping. Incredible results in a fraction of the time.
What would you build if you could spin up an AI dev team with a prompt? 🚀
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Maker
@nmime Thank you for your feedback! Really appreciate it
Report
Hey Product Hunt!
We’re Lunii, and we’ve built a B2B platform for AI-powered art creation tailored for game development studios and branding teams. Our platform is designed for professionals with very specific creative needs — it’s not just another generic AI image generator.
Splox is at the core of our system. It powers AI agents that handle almost the entire art production pipeline for us:
Automated art creation fully aligned with each client’s requirements and style guides.
A flexible editing and feedback loop, making revisions fast and seamless.
Complete production pipelines, where just one supervisor oversees the process while AI agents handle 90% of the work.
Thanks to Splox, we didn’t have to spend months building complex infrastructure from scratch. Instead, we focused on our product and clients — while Splox took care of the automation and scalability under the hood.
If you’re looking to build AI-driven workflows or products, Splox is an absolute game-changer.
Honestly, I had never used services like this before — only ChatGPT in its simplest form. But recently I decided to automate some of my work processes and couldn’t figure out how to set everything up properly. I spent several days struggling, then watched a short video — and suddenly everything worked on the first try! 🚀 Thanks @goreactdev for such a clear example.
After that, I started experimenting more: connected Google Sheets, tried building hybrid translation chains (DeepL → Google → ChatGPT), set up JSON with languages. At first I made mistakes — had to rebuild the logic from scratch, sometimes the fallback broke, and messages went into the void. But step by step, I managed to put together a minimal working setup.
What impressed me the most 🔥 — it’s incredibly simple: you just give the system a link to a Google Sheet with open access, and it instantly reads, updates, and works in real time. It sounds obvious, but in practice it really feels like a “wow-effect.”
When I hit DeepL limits, I had to manually plug in API keys and add new providers. It turned out to be easy — and the best part is, I did it myself without extra hacks. You can really feel the flexibility: you can start small and gradually scale the complexity.
Of course, not everything was smooth (for example, one of my prompts ended up being 1,400 lines long, so the Builder struggled with it 😅), but this process showed me the real potential of Splox. You can literally build working pipelines in hours, not weeks.
Overall — a super valuable experience. I’ve only just started, but I can already see this is a powerful tool for automating repetitive tasks.
I’m Alex, co-owner of a digital agency that works with small and medium-sized companies across various industries. We’ve been experimenting with Splox for the past few months, and it’s quickly become one of the most exciting platforms in our toolkit.
We started by automating some of the repetitive steps in our client interactions — handling initial messages, drafting first proposals, and pulling key insights from campaign data. From there, we extended Splox into our design and development workflows: agents now assist our designers with wireframes and asset creation, while helping our dev team with boilerplate code, QA tasks, and testing new concepts and hypotheses.
Many of our operations have benefited from this approach. We’re excited to see how Splox evolves and hope to integrate it even deeper into our processes — from ongoing client management to creating final versions of projects.
Splox has the potential to become a core part of our workflow, acting as an intelligent extension that enhances productivity and creativity across teams. We’re watching its development with great interest and hope to see Splox become a very visible and influential player in the entire industry.
I run a business in the financial sector, where speed and accuracy in working with clients and data are crucial. Integrating the product built on intelligent agents has been a key step in optimizing and scaling our operations.
The SPLOX solution has allowed us to:
-automate a wide range of routine tasks previously handled by operators;
-simplify and accelerate calculations, metrics, and reporting;
-reduce the workload on employees and let them focus on strategically important tasks;
-ensure flexibility and scalability without increasing headcount.
This tool has become a reliable assistant, significantly improving efficiency and overall performance. I highly recommend this product to anyone who values automation, control, and sustainable growth.
I'm a business manager, and Splox proved to be a lifesaver.
We were able to automate many business processes, such as client communications, sales turnover and internal management, which resulted in increased efficiency.
Thanks to the service's flexible configuration and extensive capabilities, we were able to reach the next level of organization in our structure.
Hey Product Hunt!
I’m Boris Mucha, a full-stack + ML developer. In the past, I worked a lot on developing scalable systems, including for AI pipelines. For the last 1.5 years I’ve been pouring my days and nights into Splox, because I believe AI shouldn’t work alone. Real problems need agents that can collaborate and scale — and I love building toward that future.
What started as a solo grind is now being used by early companies and over 27 testers running real multi-agent systems. One of them has 2M+ MAU — so Splox is already battle-tested at scale. I’m excited to finally launch Splox here on Product Hunt. At one stage, agents were handling about 90% of Splox’s workflows and development tasks — while I focused mainly on reviewing and tackling deeply complex parts that still require human expertise.
What you can build with Splox:
Autonomous Dev Team — all the way to full deployment on your server.
Customer support agents that handle routine tickets and escalate only when needed.
Proactive social agents — they initiate conversations, follow up, and can message you on Telegram (or other channels) or call you on your mobile.
Creative Agents — from one query, generate short-form videos, comics, or other media (script → visuals → voice → export).
Adaptive Cybersecurity Mesh — agents that develop new threat detection methods, create custom security tools for novel attacks, and continuously evolve their defense strategies by sharing intelligence with each other.
Autonomous Scientific Discovery Network — agents that formulate new hypotheses, design their own experiments, create custom analysis tools, and fundamentally change their research approaches based on discoveries.
If you’re curious about the tech side, here’s what Splox does:
Multi-agent platform — agents collaborate in parallel or sync when needed
Flexible connections — actor, orchestrator, or fully custom patterns
Sandbox environments — agents can run their own isolated sandboxes (including local MCP). They don’t just use tools, they can build and reuse them
Visual graph builder — no-code simplicity + full-code flexibility
3000+ connectors (including local mcp) — many pre-configured (LLM, image, video, TTS etc.), ready out of the box. Add your own keys anytime for advanced use
RL on top of LLMs — support for advanced adaptive agents
Agent-to-agent scheduling — agents can proactively assign and trigger each other’s tasks, enabling proactive coordination
Pricing — no subscriptions, just commission-based: pay only when your agents work
Simple examples:
MetaAgent — an agent that builds trading system by combining agents like Trader, Social Monitor, and Researcher → https://youtu.be/XcYU4bLT8TA
Frontend, Backend & QA — agents collaborating as a dev team → https://youtu.be/Ij6Nv_pTnqQ
Browser Agent — autonomous web navigation & interaction → https://youtu.be/g1qz3w1tIsM
Splox is in whitelist-only beta. Try it in 2 minutes: spin up your first agent from a template at https://beta.splox.io/templates.
Thanks for checking it out 🙏 I’ll be here in the comments all day, answering questions and sharing more about the journey.
If you had Splox today, what’s the first system you’d try building?
🤯 Built a full MVP in 4 hours instead of a month using Splox
Hey hunters! Just had to share this insane experience with Splox.
The setup: I needed to build an MVP for a client project. Usually, this would mean assembling a team, planning sprints, and delivering in 4-6 weeks.
What actually happened: I used @Splox with help of @goreactdev to build a custom multi-agent flow.
Than we set up MVP with just two prompts:
Build a working prototype based on my design specs with these features...
Add OAuth authentication and connect it to a database
That's it. The multi-agent system we created literally built the entire thing while I watched.
The agents worked like a real dev team:
Frontend Agent built React components with proper state management
Backend Agent set up APIs, database schemas, and auth flows
QA Agent found bugs I would've missed
DevOps Agent deployed everything to production
They all shared context and coordinated perfectly
They asked me clarifying questions via Telegram when needed and kept building. Frontend waited for Backend's APIs. QA tested in parallel. Like watching a senior team that's worked together for years.
What blew my mind: These agents don't just execute tasks — they actually collaborate. When the Backend agent changed an API endpoint, Frontend automatically adapted. When QA found an issue, the responsible agent fixed it without me intervening. They even suggested architectural improvements I hadn't considered.
Real talk: This isn't "no-code" or "low-code" — it's actual production-ready code written by AI agents working together. I only stepped in for critical architecture decisions.
We're living in the future where one person with the right tools can ship what used to take entire teams. Boris and the Splox team just made that future accessible.
The multi-agent flow we built together is now my go-to for rapid prototyping. Incredible results in a fraction of the time.
What would you build if you could spin up an AI dev team with a prompt? 🚀
@nmime Thank you for your feedback! Really appreciate it
Hey Product Hunt!
We’re Lunii, and we’ve built a B2B platform for AI-powered art creation tailored for game development studios and branding teams. Our platform is designed for professionals with very specific creative needs — it’s not just another generic AI image generator.
Splox is at the core of our system. It powers AI agents that handle almost the entire art production pipeline for us:
Automated art creation fully aligned with each client’s requirements and style guides.
A flexible editing and feedback loop, making revisions fast and seamless.
Complete production pipelines, where just one supervisor oversees the process while AI agents handle 90% of the work.
Thanks to Splox, we didn’t have to spend months building complex infrastructure from scratch. Instead, we focused on our product and clients — while Splox took care of the automation and scalability under the hood.
If you’re looking to build AI-driven workflows or products, Splox is an absolute game-changer.
@sindyaev Thanks for your feedback!
Honestly, I had never used services like this before — only ChatGPT in its simplest form. But recently I decided to automate some of my work processes and couldn’t figure out how to set everything up properly. I spent several days struggling, then watched a short video — and suddenly everything worked on the first try! 🚀 Thanks @goreactdev for such a clear example.
After that, I started experimenting more: connected Google Sheets, tried building hybrid translation chains (DeepL → Google → ChatGPT), set up JSON with languages. At first I made mistakes — had to rebuild the logic from scratch, sometimes the fallback broke, and messages went into the void. But step by step, I managed to put together a minimal working setup.
What impressed me the most 🔥 — it’s incredibly simple: you just give the system a link to a Google Sheet with open access, and it instantly reads, updates, and works in real time. It sounds obvious, but in practice it really feels like a “wow-effect.”
When I hit DeepL limits, I had to manually plug in API keys and add new providers. It turned out to be easy — and the best part is, I did it myself without extra hacks. You can really feel the flexibility: you can start small and gradually scale the complexity.
Of course, not everything was smooth (for example, one of my prompts ended up being 1,400 lines long, so the Builder struggled with it 😅), but this process showed me the real potential of Splox. You can literally build working pipelines in hours, not weeks.
Overall — a super valuable experience. I’ve only just started, but I can already see this is a powerful tool for automating repetitive tasks.
@shamanov Thank you very much for your feedback!
Hi Product Hunt!
I’m Alex, co-owner of a digital agency that works with small and medium-sized companies across various industries. We’ve been experimenting with Splox for the past few months, and it’s quickly become one of the most exciting platforms in our toolkit.
We started by automating some of the repetitive steps in our client interactions — handling initial messages, drafting first proposals, and pulling key insights from campaign data. From there, we extended Splox into our design and development workflows: agents now assist our designers with wireframes and asset creation, while helping our dev team with boilerplate code, QA tasks, and testing new concepts and hypotheses.
Many of our operations have benefited from this approach. We’re excited to see how Splox evolves and hope to integrate it even deeper into our processes — from ongoing client management to creating final versions of projects.
Splox has the potential to become a core part of our workflow, acting as an intelligent extension that enhances productivity and creativity across teams. We’re watching its development with great interest and hope to see Splox become a very visible and influential player in the entire industry.
@alxbit Thank you for your feedback!
I run a business in the financial sector, where speed and accuracy in working with clients and data are crucial. Integrating the product built on intelligent agents has been a key step in optimizing and scaling our operations.
The SPLOX solution has allowed us to:
-automate a wide range of routine tasks previously handled by operators;
-simplify and accelerate calculations, metrics, and reporting;
-reduce the workload on employees and let them focus on strategically important tasks;
-ensure flexibility and scalability without increasing headcount.
This tool has become a reliable assistant, significantly improving efficiency and overall performance. I highly recommend this product to anyone who values automation, control, and sustainable growth.
@ivan_ivanov47 Thank you!
Greetings Product Hunt!
I'm a business manager, and Splox proved to be a lifesaver.
We were able to automate many business processes, such as client communications, sales turnover and internal management, which resulted in increased efficiency.
Thanks to the service's flexible configuration and extensive capabilities, we were able to reach the next level of organization in our structure.
@noxygenus Thank you!