Today we're announcing that Linq is an official vendor adapter for [Chat SDK](https://chat-sdk.dev/) — Vercel's open-source TypeScript framework for building bots and agents across every major chat platform.

That means you can now build an AI agent that texts over iMessage, RCS, and SMS — using the same unified API you'd use to build a Slack bot, a Discord bot, or a Teams integration.

## What is Chat SDK?

Chat SDK is a platform-agnostic, event-driven SDK for building chat bots. It abstracts away the differences between Slack, Microsoft Teams, Google Chat, Discord, WhatsApp, and more — so you write your bot logic once and it runs anywhere.

With 1.4M weekly downloads, 2.1K GitHub stars, and 15+ adapters, it's become the standard toolkit for teams building AI-native chat experiences. It's maintained by Vercel and integrates natively with [AI SDK](https://ai-sdk.dev/) for streaming, tool calls, and structured outputs.

## What the Linq adapter adds

With `@linqapp/chat-sdk-adapter`, your Chat SDK bot gains iMessage, RCS, and SMS as delivery channels. Linq's infrastructure handles the carrier layer — your code just sees threads, messages, and reactions like any other Chat SDK adapter.

A few things worth calling out:

**Native iMessage tapbacks.** Tapbacks (like, love, laugh, emphasize, question) map to normalized Chat SDK reaction events, so your `bot.onReaction()` handlers work exactly as they would on Slack.

**Rich media support.** Inbound attachments (images, audio, files) arrive as Chat SDK attachment objects. Outbound files under 10MB are sent by URL reference; larger files up to 100MB are pre-uploaded automatically.

**HMAC-verified webhooks with replay protection.** Every inbound webhook is verified with HMAC-SHA256 and a replay-window check before dispatch. Invalid or stale signatures return 401.

**Stable thread IDs.** Every Linq chat maps to a stable `linq:{chatId}` thread ID across webhook events and API calls, so conversations don't fragment.

## How it works

Install the adapter alongside Chat SDK:

```sh
npm install @linqapp/chat-sdk-adapter chat
```

Wire it up in your bot:

```ts
import { Chat } from "chat";
import { createLinqAdapter } from "@linqapp/chat-sdk-adapter";

const bot = new Chat({
  userName: "mybot",
  adapters: {
    linq: createLinqAdapter({
      apiKey: process.env.LINQ_API_KEY,
      signingSecret: process.env.LINQ_WEBHOOK_SECRET,
    }),
  },
});

bot.onDirectMessage(async (thread, message) => {
  await thread.subscribe();
  await thread.post(`you said: ${message.text}`);
});
```

Then add a webhook route (Next.js example):

```ts
import { after } from "next/server";
import { bot } from "@/lib/bot";

export const runtime = "nodejs";

export async function POST(request: Request) {
  return bot.webhooks.linq(request, {
    waitUntil: (task) => after(() => task),
  });
}
```

Point a Linq webhook at your route and you're live — see the [quickstart guide](https://docs.linqapp.com/guides/integrations/chat-sdk/) for full setup instructions. For local dev, the [Linq CLI](https://www.npmjs.com/package/@linqapp/cli) provisions a sandbox number instantly:

```sh
linq signup
```

## Running a bot across iMessage, WhatsApp, and Telegram — from one codebase

Because Chat SDK is platform-agnostic, adding Linq as an adapter means your existing multi-platform bot logic just works. The [example app in our repo](https://github.com/linq-team/linq-chat-sdk/tree/main/apps/api) shows a single AI agent running across Linq, Telegram, and WhatsApp from one set of handlers — no branching, no per-platform glue.

## A community effort

This integration wouldn't have shipped as fast without [Fardeem Munir](https://x.com/FardeemM), a developer in the Linq community who reached out on Twitter and volunteered his time to help build it. Open source at its best — thanks, Fardeem.

## Get started

- **npm:** [`@linqapp/chat-sdk-adapter`](https://www.npmjs.com/package/@linqapp/chat-sdk-adapter) (Apache-2.0)
- **Docs:** [chat-sdk.dev/adapters/vendor-official/linq](https://chat-sdk.dev/adapters/vendor-official/linq)
- **Source:** [github.com/linq-team/linq-chat-sdk](https://github.com/linq-team/linq-chat-sdk)


Today we're announcing that Linq is an official vendor adapter for Chat SDK, Vercel's open-source TypeScript framework for building bots and agents across every major chat platform.

Linq is now a vendor-official adapter for Vercel's Chat SDK

By betting on iMessage as the channel and Linq as the infrastructure, Tomo built a deeply personal AI product for young people and scaled it from a single phone line to hundreds of thousands of messages through organic growth alone.

Tomo is a personalized AI that lives inside iMessage. It understands users' goals, affirms them, and helps them find ways to achieve those goals. The name means "friend" in Japanese, and there's a friendliness to the product that's core to why it works. Most of Tomo's users are between 15 and 24 years old, and if you try using it, the experience is, as the founders put it, "aggressively Gen Z coded."

Behind that experience is a messaging infrastructure challenge that required the right partner. With Linq, Tomo found a provider that matched their standards on reliability and security, and then kept pace as organic growth pushed their volume from a single phone line to hundreds of thousands of messages.

## From Retool to Tomo

Justin and Raymond, Tomo's co-founders, met while working together at Retool in San Francisco. About a couple of years ago, they left to start separate companies. Justin wanted to build something fun enough for a lot of people to use. Raymond wanted to build something practical with wide-scale impact on real people.

They spent about a year and a half exploring different areas before reuniting around a shared conviction: they wanted to build consumer AI products together.

> "My goal has always been to build for impact and actually deliver value to people. I think what's exciting about Tomo is just seeing that in real time." — Raymond, Co-founder

The result was Tomo: an AI that understands the user's goals, why they care about those goals, and helps them take action. It lives entirely inside iMessage, meeting young users in the app they already use every day.

![The Tomo team](https://res.cloudinary.com/linq/image/upload/v1772835185/website/Customer%20Story/Tomo/Frame_1597881371_kixvg0.png)

## Betting on iMessage

The decision to build on iMessage was straightforward. Tomo's target audience, 15-to-24-year-olds, lives inside the app. People chat a hundred times a day in a space where ten close friends and family members are already texting. For this demographic, anything other than a blue bubble feels like spam.

> "It doesn't take a rocket scientist to know that iMessage is so overpowered. It's almost so overpowered that it's difficult, because you can have a product that isn't really working, but you might think it's working just because iMessage is just so good." — Justin, Co-founder

That power cut both ways. iMessage distribution was a massive advantage, but it also meant they needed infrastructure they could trust completely. The channel was too important to get wrong.

## From building it themselves to finding Linq

Tomo's engineering team was confident. They had phones from other projects, strong technical chops, and the conviction that they could build iMessage infrastructure in-house. They got something working quickly. But it didn't last.

They evaluated providers across multiple companies. The conclusion was clear: the folks at Linq were the best people for the job. The evaluation criteria came down to security, latency, reliability, and price. But above all, Tomo optimized for reliability.

> "You can build a lot of trust for users over 2,000 messages, but it only takes two or three message failures, or even just one, to break that trust."

## When users start caring about privacy, you're winning

Tomo's users share deeply personal information through the product. The things they use Tomo for — their goals, their struggles, their daily lives — are hyper personal. That creates a real obligation around data security, and it makes compliance like SOC 2 matter in practice, not just on paper.

What surprised the team was an emerging signal they didn't expect. As users went deeper into the product, they started asking about data privacy. Not because something went wrong, but because they'd shared so much that the question became personal.

![Tomo on iMessage](https://res.cloudinary.com/linq/image/upload/v1773084933/website/Customer%20Story/Tomo/Tomo_phone_esv06s.jpg)

## From a single phone line to hundreds of thousands of messages

Tomo launched with a single phone line. The first users were the founders themselves, testing with friends, watching hundreds of messages flow through each day, and asking the fundamental question: does this thing have legs?

It did. When the team started promoting on TikTok and Instagram Reels, where their users actually live, demand took off. Through it all, the Linq team kept pace. Five months in, they went from hundreds of messages a day to hundreds of thousands.

## Engagement and retention that finally work

Justin and Raymond have built many consumer products before. But Tomo is the first time they've seen engagement and retention levels where things are clearly starting to work.

The team is now focused on making Tomo more helpful and fun to use with friends. One example: group chats — currently a hidden feature that only the most curious users have discovered, but one the team sees as a natural extension of the product.

## What's next

Tomo's story is still early. The team sees a massive opportunity to scale the product's impact across millions of people, and they're hiring across growth, ops, and engineering to get there. The infrastructure that Linq provides — reliable, secure, and able to scale on demand — is what lets them focus on the product instead of the plumbing.

> "The folks at Linq have always been super gracious and helpful and super responsive. That's been the case whenever we've needed to grow." — Justin, Co-founder, Tomo

How Tomo built a deeply personal AI for young people on iMessage and scaled it from a single phone line to hundreds of thousands of messages on Linq infrastructure — through organic growth alone.

Tomo and Linq: How a Personalized AI for Accountability Scaled to Hundreds of Thousands of Messages

By treating iMessage as their primary UI and choosing Linq for security, zero data retention, and on-demand scalability, the team behind Poke built a product that scaled entirely through word of mouth — without ever worrying about infrastructure.

The Interaction Company of California builds Poke, a consumer product that treats iMessage as its primary interface. Users don't download an app. They chat. What started as a tool for managing email inside iMessage has evolved into something much broader: a conversational AI that people use for school, daily planning, and personal support.

Founded by Felix and Marvin, two German immigrants who moved to the Bay Area to start a company, the team knew from the beginning that iMessage was the channel. The question was who to trust with the infrastructure that would make it work.

> "We are treating iMessage and SMS as our first-party UI for interacting with our product. That's a space that not very many other companies work in." — Felix, Co-founder

With Linq, the team found the infrastructure partner that made that bet possible and kept pace as organic growth pushed their messaging volume through multiple orders of magnitude.

## Building a product thesis around iMessage

The original idea was straightforward: build something that triggers on every email notification, summarizes the important ones, and lets users act on them without opening an email client. But the team quickly realized people didn't want another email interface. They wanted to interact with email inside the messaging app they already used a hundred times a day.

Samyok, a Member of Technical Staff at the company, joined after interning at Robinhood and Jane Street. He'd been trying to figure out what to do after his last semester when he saw Poke's product thesis in action.

> "When I saw this opportunity, I saw that this product thesis actually works. I decided to join and take a bet. And so far it's paid off really well." — Samyok, Member of Technical Staff

As adoption grew, the team discovered that email was just a fraction of what people used Poke for. Users connected all sorts of services. They used it for school. They used it to chat when they had problems. The product had taken on a life of its own.

![Inside Poke](https://res.cloudinary.com/linq/image/upload/v1772820868/website/Customer%20Story/Poke/CleanShot_2025-09-22_at_09.28.23_1_dkabty.png)

## A waitlist that felt like the product

When it came time to launch, the team faced a constraint: high inference costs meant they had to restrict access. But they didn't want a simple waitlist. Instead, they built something that lived inside the same channel as the product itself.

Users chatted with Poke's bot in iMessage, tried to convince it to give them access, and simultaneously haggled for a good price. The waitlist wasn't a gate. It was a preview of the entire product experience.

## Finding a provider that checked every box

Treating iMessage as a primary UI meant the messaging provider wasn't just infrastructure. It was the product. The team's evaluation criteria reflected that. Functionality came first, then security, then price. They needed SOC 2 compliance, zero data retention, and a provider they could trust.

They searched extensively. Other providers surfaced, but none met the full requirements. Some lacked SOC 2. Others couldn't support zero data retention. Some were significantly more expensive.

> "We did a ton of searching, and we only found Linq to be able to fit all three of these criteria."

The stakes were made viscerally clear before the team even found Linq. While using a previous messaging provider, Poke's messages were flagged as spam. The provider blocked all of Poke's messages for every user, on the day the company closed its fundraise. The experience underscored why the right provider wasn't optional. It was existential.

## Going live with Linq, and building together

Implementation was fast. The team added Linq as a provider with minimal lift, and the first phone line was up and running quickly. But what made the relationship distinctive was what came after onboarding.

Linq built zero data retention specifically for the team, and maintained a tight feedback loop, shipping features in direct response to requests. When someone casually mentioned a Find My location feature, Linq had it done within a week.

![Poke product in action](https://res.cloudinary.com/linq/image/upload/v1772836605/website/Customer%20Story/Poke/Poke_phone_zgsv4m.jpg)

## Scaling through word of mouth, without worrying about infrastructure

The team started in April with a single phone line and a small test group. Growth came in waves: first one line, then around twenty, then hundreds right before launch. Every expansion was driven by organic demand.

Within days of joining the Linq platform, the team was processing ten thousand messages in a single day. From their perspective, the experience was seamless. "It feels like a cloud provider," they say. "We can request a large number of numbers, and you guys just accommodate everything and get it done within a couple of days."

## Launch night

For Felix, the most memorable moment of the past year was launch night. The team pulled an all-nighter. It was hectic. And then the next day, the numbers spiked alongside a wave of positive user feedback that the team says they'll never be able to recreate.

## Infrastructure that lets a team focus on what matters

The team has scaled through multiple orders of magnitude since joining Linq. Instead of planning around infrastructure constraints, the team focuses on product and growth: expanding use cases beyond email and building new interaction models.

> "It feels like a cloud provider. Every time we put in a new order for more capacity, Linq just scales with us. I think there are a lot of other providers on all parts of our infrastructure that would not be able to keep up." — Felix, Co-founder, The Interaction Company of California

How The Interaction Company of California scaled iMessage-based AI with Linq — zero data retention, SOC 2 compliance, and on-demand scalability that kept pace with viral, word-of-mouth growth.

Tomo and Linq: How a Personalized AI for Accountability Scaled to Hundreds of Thousands of Messages

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Linq is now a vendor-official adapter for Vercel's Chat SDK

Tomo and Linq: How a Personalized AI for Accountability Scaled to Hundreds of Thousands of Messages

The Interaction Company of California and Linq: How Poke Scaled Messaging

Linq Blog

Tomo and Linq: How a Personalized AI for Accountability Scaled to Hundreds of Thousands of Messages

Latest Posts

Linq is now a vendor-official adapter for Vercel's Chat SDK

Tomo and Linq: How a Personalized AI for Accountability Scaled to Hundreds of Thousands of Messages

The Interaction Company of California and Linq: How Poke Scaled Messaging