AI Hive

The no-code platform that gets AI agents into production

5.0•13 reviews•

108 followers

The no-code platform that gets AI agents into production

5.0•13 reviews•

108 followers

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AI Workflow Automation

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AI Engineer

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No-Code AI Agent Builder

AI Hive is an AI-powered no-code platform that makes enterprise AI agent deployment seamless. Easily build agents across any LLM (GPT, Claude, Gemini, Llama), orchestrate multi-agent workflows with a drag-and-drop builder, deploy on cloud, on-prem, or white-label, connect 50+ integrations, use 500+ ready-made templates, and ship to production in days with enterprise-grade compliance built in. Get AI agents from demo to production without hiring an internal AI team!

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Launch tags:SaaS•Artificial Intelligence•Tech

Launch Team / Built With

Maker

📌

I want to tell you how AI Hive actually started — because it didn't begin with a whiteboard or a funding round.
It started with an eCommerce chatbot in Vietnam.
A few years ago, I built ChatX (chatx.vn) — an AI chatbot for Vietnamese online stores. No grand vision. Just a real problem I kept seeing: small stores were drowning in repetitive customer messages and had nothing built for them to handle it automatically. ChatX grew to around 2,000 users, all organic, all Vietnamese, all just trying to save time.
It worked. But it had a ceiling. It was still just a chatbot.
Then I joined AHT Tech — an enterprise IT outsourcing company with 18+ years of delivery experience working with large organisations across Southeast Asia.
That changed my perspective completely.
I went from talking to eCommerce store owners to sitting across the table from operations leads at banks, hospitals, and logistics companies. These were organisations running SAP, Salesforce, decade-old internal systems — and they were all trying to figure out how to actually deploy AI, not just experiment with it.
What I kept seeing was the same problem, just at a different scale: the tools available either assumed you had a team of AI engineers, required months of implementation, or couldn't run inside the company's own infrastructure — which for regulated industries isn't a preference, it's a hard requirement.
I kept thinking about ChatX. About how fast I could go from idea to something real that users actually touched. And I started asking: what would that speed look like if we built it seriously — with proper integrations, governance, and the flexibility enterprises actually need?
That's the question AI Hive is the answer to.
No-code Studio, Workflow and ChatFlow builders, multi-agent orchestration, 50+ integrations across ERP, CRM, eCommerce, and support platforms, and deployment options that include on-premise for organisations that can't move their data to an external cloud.
AI Hive is what ChatX grew into — built for the version of the problem I didn't fully understand until I was inside an enterprise trying to solve it.
We're live in Singapore, UAE, and Vietnam. Today is the day we open it up wider.

If you're:

→ Struggling to move AI from pilot to production

→ In a regulated industry where data can't leave your network

→ Tired of tools that require 6 months of implementation

...we built this for you.

Ask us anything below 👇 — or try it free at AI HIVE

— Nolan & The AI Hive Team

Learn more at aihive.global

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7mo ago

Spycost

🧐 Good find

Looks like a practical way to move AI agents from demos into real production workflows. What was the hardest part of making this enterprise-ready?

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3mo ago

Maker

@glebarios Appreciate you asking, honestly this is the question we get the least and think about the most. The hardest part wasn't the AI or the agent logic at all, it was governance: getting PII masking, RBAC, and audit trails solid enough that a compliance team wouldn't kill the project before it even got a fair shot. Multi-agent orchestration was actually the fun part, the boring plumbing around access control and data residency is what actually decides if this survives procurement.

Thanks for the thoughtful question, it's exactly the kind of feedback we asked for. Really glad this landed as practical rather than just another AI pitch.

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3mo ago

Maker

Quick update for anyone who's been following along. We're getting ready to launch the next major version of AI Hive on Product Hunt in the coming weeks. This release brings everything we've been working on based on feedback from real enterprise users: multi-agent orchestration, on-prem deployment options, deeper governance controls, and an expanded marketplace of pre-built agent templates.

Honestly, the past few weeks of getting roasted on positioning, pricing, and homepage clarity have shaped this launch more than any internal review meeting ever could. So this is a genuine ask to the PH community: if you've got feedback, suggestions, or even harsh opinions on what enterprise AI platforms should actually do better, we'd love to hear them before we go live.

If you want to support the launch when it drops, follow us here: https://www.producthunt.com/products/ai-hive. Every upvote, comment, and review from this community means a lot to a small team trying to build something real in this space. Thank you in advance, seriously.

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4mo ago

Forum Threads

p/ai-hive

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3d ago

Q&A, the production AI ops questions we get asked most and the honest answers

Compiling the production AI ops questions we get asked most often from prospects and customers. Sharing the honest answers.

Q: How do you handle a model deprecation by the LLM vendor?

A: Multi-LLM routing means no single deprecation breaks our platform. Customers running BYOM are responsible for their own model lifecycle.

p/ai-hive

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7d ago

AMA for founders building AI products, what I've learned shipping into enterprise

For founders looking at the enterprise AI market, sharing what I've seen from the platform side.\

Topics I can speak to:

p/ai-hive

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10d ago

Ask me anything about enterprise AI deployment, compliance, on-premise, or AI Hive specifically

Opening this up for the community. I work on enterprise AI agent deployments, mostly mid-market through enterprise BFSI, healthcare, retail, and logistics.

Topics I'm happy to go deep on:

- Pilot-to-production gap and how to close it

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