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Company profile · 3 min read

Chert: programmable iMessage conversations for businesses

iMessage infrastructure with APIs, webhooks, context, attachments, group threads, and SMS/RCS fallback.

Published · Updated

Chert makes iMessage programmable for businesses that want customer conversations to feel native rather than like automated SMS. The buyer decision is whether trusted, two-way iMessage threads are worth the operational work of verified identities, fallback channels, consent, and volume controls.

What it does

Chert says teams can send and receive iMessages through an API, preserve reply context, support typing and reactions, attach files and contact cards, run group threads, fall back to SMS or RCS, and receive delivery events through webhooks. Its examples cover customer experience, sales, scheduling, and B2C workflows (Chert homepage; YC launch).

Fact What the public sources say
Buyer B2C startups, customer-experience teams, sales teams, and agent builders
Channel Native iMessage with SMS/RCS fallback when needed
API REST endpoints, webhooks, message status, attachments, and context are listed
Operational controls The company describes identity warming, per-identity volume caps, and spam-avoidance practices
Founders Gary Gao and Ian Fong

Why it fits

The value is the channel experience. A business can start a conversation in a familiar blue-bubble thread, keep the history available to an AI or human, schedule an appointment, send a document, and push the result back into its CRM. That is a different job from sending a one-way notification or building a custom device farm.

The tradeoff is that iMessage is a controlled ecosystem, not an unlimited outbound pipe. Chert's own FAQ says it rotates sending identities, warms them gradually, and caps daily volume; a buyer should resolve identity ownership, consent and opt-out, deliverability, account suspension, fallback behavior, geography, message recording, and how group threads map to customer records (Chert homepage). Pricing was not published.

The founders bring technical and systems context. YC describes Gao as a Penn CS and business student who researched ML and hardware, and Fong as an NYU math/CS/economics student with fast-algorithm research and hackathon experience (YC company profile).

Short version: Chert is compelling when a customer conversation needs to feel personal and two-way. Start with a narrow appointment or service workflow before making it a core outbound channel.

Sources checked — 2026-09-19

Cohort context

Chert is listed in Spring 2026. In our 2026-09-18 directory snapshot, 112 of 193 listed companies in that cohort have YC’s primary industry label B2B (58.0%). This is a current-directory comparison, not an original intake count or a performance ranking. Nine-cohort dataset.

Public website snapshot

Observed 2026-09-19T16:16:09.193Z in raw homepage HTML. This records visible metadata and advertised links, not agent execution or product quality.

Signal Homepage observation
Product description metadata Observed
Canonical link Observed
H1 or H2 heading Observed
Typed structured data Observed
Docs/developer link Observed
Pricing link Not observed in this response
llms.txt link Not observed in this response
Markdown alternate Not observed in this response

Public observations · Collection method. Missing links here do not establish that a capability or file is absent elsewhere.

About the author

I cofound Lazyweb and publish Mudpie. This is an owner-written publication, not an independent testing organization. Research notes distinguish observations, sourced reporting and editorial judgment.

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