Build agent for your customers, run workflows, analyzed.
Build multichannel AI chat and voice agents for your website, Telegram, and beyond. Create specialized sub-agents to orchestrate workflows across your knowledge bases, datastores, and hundreds of third-party tools in real time. Automatically evaluate every interaction, score lead quality, and extract structured data straight from conversation transcripts.
Full disclosure: I originally built Embage to launch a one-person company. I picked customer support because reps spend way too much time on repetitive tasks, sifting through docs, processing returns, and sending standard emails.
With Embage, AI agents handle all of that autonomously. If anything critical comes up, your human team can step in whenever the agent requests a handoff.
The Vision: My goal with Embage is to give lean teams from e-commerce stores to local service providers, the power to run fully automated, multi-step operations without needing dedicated dev support.
To make this happen beyond basic support, we built Custom Datastores. Datastores let you create custom tables to store whatever data your agents collect, like tickets, leads, or feedback. Simply create a datastore, build your main agent, link a sub-agent with rules on when to use that data, and you're good to go!
You don't need paid Embage plan to build ai agent. On the free plan, you can simply plug in your own API keys and run your agents directly without any AI credit markups.
Embage is still early. If you spot any bugs or need a feature, let us know, I’ll patch or build it as fast as possible.
Give Embage a try using code "LAUNCH_FREE" to claim free AI credits and build your first agent. Excited to hear your feedback!
About Embage on Product Hunt
“Build agent for your customers, run workflows, analyzed. ”
Embage launched on Product Hunt on November 1st, 2026 and earned 170 upvotes and 12 comments, placing #4 on the daily leaderboard. Build multichannel AI chat and voice agents for your website, Telegram, and beyond. Create specialized sub-agents to orchestrate workflows across your knowledge bases, datastores, and hundreds of third-party tools in real time. Automatically evaluate every interaction, score lead quality, and extract structured data straight from conversation transcripts.
On the analytics side, Embage competes within Telegram, Customer Communication and Artificial Intelligence — topics that collectively have 501.1k followers on Product Hunt. The dashboard above tracks how Embage performed against the three products that launched closest to it on the same day.
Who hunted Embage?
Embage was hunted by Aradhya Tiwari. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Embage including community comment highlights and product details, visit the product overview.
Aradhya Tiwari
Hi Product Hunt! 👋
I’m Aradhya, maker of Embage.
Full disclosure: I originally built Embage to launch a one-person company. I picked customer support because reps spend way too much time on repetitive tasks, sifting through docs, processing returns, and sending standard emails.
With Embage, AI agents handle all of that autonomously. If anything critical comes up, your human team can step in whenever the agent requests a handoff.
The Vision: My goal with Embage is to give lean teams from e-commerce stores to local service providers, the power to run fully automated, multi-step operations without needing dedicated dev support.
To make this happen beyond basic support, we built Custom Datastores. Datastores let you create custom tables to store whatever data your agents collect, like tickets, leads, or feedback. Simply create a datastore, build your main agent, link a sub-agent with rules on when to use that data, and you're good to go!
You don't need paid Embage plan to build ai agent. On the free plan, you can simply plug in your own API keys and run your agents directly without any AI credit markups.
Embage is still early. If you spot any bugs or need a feature, let us know, I’ll patch or build it as fast as possible.
Give Embage a try using code "LAUNCH_FREE" to claim free AI credits and build your first agent. Excited to hear your feedback!