Build and deploy conversational iMessage agents for customer service, inbound lead capture, and more. Simply configure the system prompt and tone, and you can create your own conversational iMessage agent for inbound handling, outbound follow-up, or whatever workflow you want to test. You can also integrate with CRMs like HubSpot, Close, or GoHighLevel to write back conversation histories.
We've spent the last six months building projects on iMessage for leasing companies, DTC startups, and home service agencies. Across these use cases, we kept seeing the same problem. Founders wanted to deploy conversational iMessage agents for customer service, lead capture, and outbound follow-up, but the underlying infrastructure was difficult to set up and hard to scale reliably.
This is what inspired us to build Chert, a platform for teams to create and deploy iMessage agents, powered by infrastructure that can send, receive, and automate conversations over iMessage at scale. There's a few main features that we believe will make Chert stable, reliable, and scalable:
- Chert provides comprehensive line health checks, making it safer and more robust for outbound use cases. - Additionally, Chert offers a scalable pricing structure that lets teams scale to hundreds of lines and thousands of messages. - Finally, Chert integrates with CRMs like Salesforce, HubSpot, and Close and tools like Vapi and Slack, so teams can easily add iMessage into their existing stacks at scale.
Feel free to try building and deploying your own iMessage agent through the Agents page in our website. No credit card required.
Hey, was reading through Chert's site and the iMessage-as-support-channel framing is honestly wild. one thing I wanted to understand, what's the path for non-iPhone customers, is there an SMS fallback or is the product fully iOS-only by design? that fork basically defines whether this is niche or omnichannel.
Congrats on the launch! How would love to understand more how the inbound/outbound mechanism work? Is it basically an agent for each use case? Is the skill included out of the box?
Really cool. What are ur thoughts on trust and user experience? iMessage feels valuable rn bcs
its not yet flooded with business messaging slop.
Do people usually use Chert to replace sms or have you seen circumstances where people use
both sms/rcs and blue-bubble messaging?
What is the difference between Chert and SMS/RCS other than blue-bubble messaging?
Love this! AI agents in a channel people already trust feels much more compelling than yet another app download. Can the agent proactively message users too, or is the product more focused on responding once a conversation begins?
iMessage open rates are hard to beat. How does the underlying send mechanism work exactly? Apple doesn't have a public business API for iMessage - is this throught Apple Business Chat, a Mac relay, or something else?
Why only iMessage? We recently had a client asking us to build a similar service, but connected to all popular messengers and social networks for handling customer requests, which would then also be sent to the CRM. We looked for a ready-made solution, but couldn’t find anything that supported all the platforms they needed.
Getting iMessage delivery working for AI agents is a non-trivial integration challenge since Apple doesn't expose a public API. We've wrestled with customer communication channel tradeoffs at RetainSure, and iMessage reach in B2C contexts is real. How are you handling message delivery guarantees and rate limits at scale when the underlying transport doesn't give you standard webhook callbacks?
Building on iMessage means dealing with Apple's undocumented protocol quirks, and wrapping that behind a clean API is the real product. We've been building customer-facing AI agents at RetainSure and delivery reliability across channels is a constant headache. How do you handle delivery confirmations in iMessage? Does the API surface read receipts or are you inferring from response patterns?
The iMessage delivery angle is smart. B2B tools rarely nail async customer touchpoints, but buyers actually respond to texts. We're running customer success workflows at RetainSure and the biggest gap is getting responses to renewal nudges. CRM write-back via HubSpot is a nice touch. Does the agent handle multi-turn conversations well, or does it reset context between sessions?
Big congrats on the launch. What does the integration actually look like? Is it mostly configuring the agent prompt and workflow in the dashboard, or do teams usually connect it into their existing stack too?
Are you routing through registered businesses with iMessage for Business or solving it some other way? The leasing companies angle is sharp positioning. SMS open rates collapsed in the last couple years for those verticals and iMessage actually moves the needle here
Could see this being really useful for businesses that get a lot of inbound interest. Are people using Chert to capture new demand right now or to mainly convert old demand they already missed?
@garygao Congrats on the launch! Really interesting product. Is there a way to try building an agent before talking to sales? I’d love to send a few test messages and see the developer flow end to end.
About Chert on Product Hunt
“Build AI agents that text customers in iMessage”
Chert launched on Product Hunt on May 19th, 2026 and earned 171 upvotes and 77 comments, placing #7 on the daily leaderboard. Build and deploy conversational iMessage agents for customer service, inbound lead capture, and more. Simply configure the system prompt and tone, and you can create your own conversational iMessage agent for inbound handling, outbound follow-up, or whatever workflow you want to test. You can also integrate with CRMs like HubSpot, Close, or GoHighLevel to write back conversation histories.
Chert was featured in Messaging (51.9k followers), API (98.2k followers) and Artificial Intelligence (468.8k followers) on Product Hunt. Together, these topics include over 116.4k products, making this a competitive space to launch in.
Who hunted Chert?
Chert was hunted by Garry Tan. 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.
Want to see how Chert stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Garry Tan
Hi everyone, I'm Gary, co-founder of Chert!
We've spent the last six months building projects on iMessage for leasing companies, DTC startups, and home service agencies. Across these use cases, we kept seeing the same problem. Founders wanted to deploy conversational iMessage agents for customer service, lead capture, and outbound follow-up, but the underlying infrastructure was difficult to set up and hard to scale reliably.
This is what inspired us to build Chert, a platform for teams to create and deploy iMessage agents, powered by infrastructure that can send, receive, and automate conversations over iMessage at scale. There's a few main features that we believe will make Chert stable, reliable, and scalable:
- Chert provides comprehensive line health checks, making it safer and more robust for outbound use cases.
- Additionally, Chert offers a scalable pricing structure that lets teams scale to hundreds of lines and thousands of messages.
- Finally, Chert integrates with CRMs like Salesforce, HubSpot, and Close and tools like Vapi and Slack, so teams can easily add iMessage into their existing stacks at scale.
Feel free to try building and deploying your own iMessage agent through the Agents page in our website. No credit card required.
Would love any feedback or thoughts!