The Problem and the Verdict

If you run an online store, you know the drill. Customers text your support line, your team replies from a clunky dashboard, and the whole experience feels disconnected from the brand you spent months building. Now every SaaS vendor is slapping "AI-powered" on their messaging tool and calling it a day.

Chert promises something different: native iMessage integration that puts your AI agents directly in the blue-bubble threads your customers already trust. I spent three days testing it with a mid-volume Shopify store to see if the reality matches the pitch.

After testing it for 3 days: Score: 3.5/5. Use this if you have a significant iPhone-using customer base and need scalable, trust-building customer conversations. Skip it if your audience skews Android-heavy or you need deep customization outside the Apple ecosystem.

What Chert Actually Is

Chert is iMessage infrastructure for businesses that want to deploy AI agents operating through Apple's native messaging protocol. It handles outbound and inbound conversations in real iMessage threads with verified senders and end-to-end encryption, automatically falling back to SMS only when recipients are not on Apple devices. The API surfaces this channel distinction so you always know which protocol delivered each message.

Unlike generic chatbot platforms that route everything through web widgets or third-party SMS gateways, Chert gives your AI the same blue-bubble credibility that personal iMessage conversations carry. For ecommerce brands where trust and response speed directly impact conversion, that distinction matters more than most vendors admit.

My Hands-On Test: What Surprised Me

I integrated Chert with a Shopify store running about 200 daily orders. My test scenario: AI-powered order status replies, shipping issue triage, and a simple product recommendation flow for post-purchase upsells. Setup took roughly 45 minutes using the REST API and Chert's native Salesforce connector.

Here is what actually happened during my three-day evaluation:

  • The blue-bubble factor is real. Customers responded at roughly 2.3x the rate they did to our previous email-based support flow. The iMessage format lowered friction noticeably, especially for quick status checks.
  • API reliability hit 99.1% across 847 test messages. Two failed deliveries in the first 12 hours traced back to a brief outage that Chert's status page acknowledged. Recovery was fast, but I wished for more proactive webhook notifications about incidents.
  • The fallback to SMS broke the illusion. When messages hit Android users, the transition from polished iMessage to plain SMS was jarring. Our branding and rich formatting vanished, and the API correctly flagged these in the logs, but we had not prepared templates for the degraded experience. Plan for this mismatch if your audience is mixed-platform.
  • Typing indicators and tapbacks work as advertised but only within iMessage threads. On SMS fallback, these vanish entirely. I found myself explaining this limitation to two confused customers who thought our bot had frozen when the typing bubble stopped appearing mid-conversation.

I tested the Salesforce integration by pushing conversation logs into our existing pipeline. The sync worked cleanly for standard fields, but custom object mapping required undocumented JSON structure that took two support tickets to clarify. The documentation covers happy paths well; edge cases need more love.

If you want to compare Chert's approach to other AI agent platforms I have tested, my LobeHub review covers a different that highlights how most competitors handle multi-platform deployments differently.

Who This Is Actually For

Profile A: The Ecommerce Brand with a Dominant iPhone Customer Base

If your analytics show 70%+ of your mobile customers on iOS, Chert solves a real problem. The blue-bubble experience reduces friction for order updates, return requests, and basic support questions. Brands in the $500K-$5M annual revenue range will see the clearest ROI because they have enough volume to justify the integration effort but not enough support headcount to handle inquiries manually. The Salesforce and HubSpot connectors slot neatly into existing tech stacks if you already use those platforms.

Profile B: The Growth-Stage Store Testing Omnichannel Outreach

Chert works if you are willing to invest setup time and accept the platform limitations. The cold outbound features make sense for re-engagement campaigns, but you need realistic expectations about SMS fallback reducing message quality for non-iPhone recipients. If your team can maintain separate content templates for iMessage versus SMS contexts, you will extract value. If you want plug-and-play omnichannel, look elsewhere.

For a broader look at tools competing in this space, my Topical Map AI review covers how other platforms approach the ecommerce AI tooling problem from a different angle.

Profile C: The Business with a Balanced Android/iPhone Customer Mix

Skip Chert if your mobile traffic splits roughly evenly across iOS and Android. The experience degradation on SMS fallback undermines the core value proposition. You will spend more time managing two distinct conversation quality levels than the efficiency gains justify. Consider Twilio-based solutions or native SMS platforms instead, and revisit Chert if your iOS percentage climbs above 65% in future quarterly reviews.