Launched this week
Teamily AI
Your personal agent, agent teams & people in one messenger
1K followers
Your personal agent, agent teams & people in one messenger
1K followers
The human-agent platform where people and always-on agents get work done together in one unified, context-aware space. Unlike single-user personal agents, Teamily AI enables multi-user, multi-agent teamwork. Built on an AI-native messenger, it connects people, agents, docs, meetings, calls, workflows, and business systems to automate office work and customer service. Agents become real teammates with persistent memory, proactive intelligence, and continuous self-improvement. Free to get started.
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Promoted
👋 Hi Product Hunt! I'm Aiden, CEO of Teamily AI. I'm excited to introduce the latest version of Teamily to the Product Hunt community and share our vision for its future.
Today, Teamily AI brings people and AI agents together through a multi-user, multi-agent collaboration platform built on a reinvented AI-native messenger. It’s a faster and smarter way to turn conversations into creations and automations, from web apps and slide decks to deep research, dashboards, documents, videos, and more, with connected context, living memory, and self-improving AI agents.
But our ambition goes far beyond a human-agent collaborative platform.
Teamily AI's long-term vision is to build the central platform of the next-generation Agentic Internet, where services and work are delivered by AI agents, no longer wrapped inside traditional web, desktop, or mobile apps distributed through app stores or search engines. Agent-as-a-service (AaaS) will be as accessible as friends on a social network. Just as Google democratized access to information and services in the web era, Teamily AI aims to democratize access to intelligence and services in the Agentic Internet era, making the right intelligence, people, and services equally accessible to everyone.
We’d love to hear your feedback!
Keeping feedback attached to the exact draft would help in a shared chat. The next person joining the conversation needs to know which version everyone reviewed.
@oleksii_sekundant Yeah, otherwise the first thing you have to ask is “Wait, which draft are we talking about?” Keeping the comments with the version people actually reviewed would save a lot of scrolling.
@oleksii_sekundant Oleksii yes!! and late joiners are the real test 😅 if they can't tell which version got the thumbs-up, the whole thread is just noise to them. keeping feedback pinned to the exact draft is one of the things I care most about getting right
Getting a finished research task back in the group thread sounds handy. Everyone can see the result and ask questions together. Nice work!
@marianna_tymchuk right, many of our enterprise customers teach each other the usage of AI in the way you described.
@marianna_tymchuk thanks Marianna!! that's exactly the moment we designed for, the result lands where everyone already is, so the questions happen together instead of in five separate DMs 😄 and if you want to go further, Agent Loop lets you build your team's own workflow on an open canvas!
The human approval flow will probably decide how comfortable teams feel using this.
@ibitekukie Yeah, if an agent drafts a client reply in the group chat, the team can read it and decide what actually goes out. I’d want that to feel as easy as asking a coworker, “Can you take a look before I send this?”
@ibitekukie Agree Chenyue 💯 Approving has to feel lighter than doing it yourself, otherwise nobody hands anything off. I think of it like asking a coworker "can you look before I send this?", quick, clear, and you know exactly what you're saying yes to.
Our project context is always scattered between chat, docs, and task tools. Keeping it together would help.
@irving_ai Yeah, the task says what changed, but the reason is buried in a chat from two weeks ago. We built Teamily AI around the idea that when you tag an agent, you shouldn’t have to piece that story together for it every time.