1. Headline & intro
The next big AI platform shift might not be a shiny new app, but a blue bubble in the same chat list where you text your friends. With a fresh $20 million in Series A funding, Linq is betting that AI assistants should live inside iMessage, RCS and other messaging apps — not in standalone apps that users forget after a week.
In this piece, we’ll look at what Linq actually does, why investors are excited, how this reshapes the infrastructure layer under conversational AI, and what it means for European markets where WhatsApp, not iMessage, rules the phone screen.
2. The news in brief
According to TechCrunch, Birmingham-based startup Linq has raised $20 million in Series A funding led by TQ Ventures, with participation from Mucker Capital and angel investors. The company, founded by former Shipt executives, originally built a digital business card and sales tool but pivoted to messaging infrastructure.
In early 2025 Linq launched an API that lets companies talk to customers directly inside iMessage (and also via RCS and SMS), using native features like group chats, images and voice notes. That product quickly gained traction: TechCrunch reports Linq doubled the annual recurring revenue it had built over four years in just eight months.
A viral iMessage AI assistant called Poke, built by a customer, triggered a further pivot. Linq now positions itself as infrastructure for AI agents living inside messaging apps. The company says it handles over 30 million messages per month, powers AI agents with 134,000 monthly active users, grew its customer base 132% quarter-on-quarter, and claims 295% net revenue retention with no churn.
3. Why this matters
Linq is quietly attacking two pain points at once: app fatigue for users and channel fragmentation for developers.
For consumers, the pattern is familiar: every new AI assistant arrives as yet another app or web interface. Most never make it to the dock. Messaging, by contrast, is opened dozens of times per day. If AI can live where your social and work conversations already happen, the barrier to trying — and reusing — new agents collapses.
For developers and companies, the current AI landscape is upside-down. Building a good assistant is already hard: you need model orchestration, retrieval, integrations, guardrails. On top of that, you’re expected to ship native apps, maintain web frontends and wire up SMS or WhatsApp on the side. Linq’s bet is that a “messaging-native” interface can be the primary front door for many AI products.
This reframes Linq less as a Twilio clone and more as an “AI-first Twilio”. Twilio and similar players made it trivial to send and receive messages; Linq is optimising specifically for continuous, agentic conversations where an AI, not a human, is usually on the other side.
Who wins?
- AI startups that want distribution inside familiar channels without negotiating every carrier and platform.
- Brands and SMEs that can offer AI-powered customer service and sales without training call centres or launching new apps.
Who loses?
- Standalone AI apps that rely on users discovering and remembering one more icon.
- Legacy CRM and contact-centre vendors who still treat chat as a bolt-on, not as the primary interface.
The most important implication: if messaging-native AI becomes normal, the “app” stops being the unit of competition. The contact in your inbox — and the quality of the conversation — becomes the product.
4. The bigger picture
Linq’s pivot sits at the intersection of three converging trends.
1. The rise of autonomous AI agents.
Recent viral products like Poke and Moltbot (formerly Clawdbot), as covered by TechCrunch, show that people are willing to delegate complex, ongoing tasks to AI that behaves more like a lightweight employee than a one-shot chatbot. Those agents need persistent, low-friction channels where users can drop in new instructions and get updates. Messaging is ideal for that.
2. Messaging as the universal UX.
We’ve already seen one failed hype cycle: the 2016 Messenger bot wave, when everyone from restaurants to airlines built rigid script-based bots for Facebook Messenger. The UX was clunky because the bots were dumb and heavily menu-driven. The difference now is that large language models can handle open-ended conversations, and users have also been trained by WhatsApp, Slack and Discord to treat chat as an everything-interface.
3. Infrastructure for AI, not just AI models.
Investors have started to realise that the picks-and-shovels around AI — data pipelines, orchestration, observability and now distribution — may be more defensible than yet another wrapper on top of GPT-4. Linq is positioning itself in that picks-and-shovels layer for communication: it doesn’t care which model you use, only that your AI can talk to humans over any channel.
Compared with Twilio, Vonage or MessageBird, Linq’s differentiation is less about raw channel coverage and more about opinionated support for agent workflows: identity, sessions, context, potentially billing and CRM integration down the line. If they execute well, they become the default wiring for “talk to my users wherever they are”, just as Stripe became the default for “accept payments online”.
But there’s a shadow side: as TechCrunch notes, Linq is currently heavily dependent on Apple’s platform. Apple could decide that third-party AI agents inside iMessage are a competitive risk and change the rules, just as Meta has done repeatedly with Facebook’s platform access. Platform risk is not a theoretical concern; it’s existential.
5. The European / regional angle
From a European perspective, the story gets more complex — and more interesting.
First, iMessage is a minority player in most EU markets. WhatsApp dominates consumer messaging in countries like Spain, Germany and Italy; Telegram and Signal have strong niches in privacy-conscious communities and Eastern Europe. Any infrastructure layer that wants to matter here must treat iMessage as one channel, not the channel.
Linq’s roadmap — supporting WhatsApp, Telegram, Signal, Slack and email — is therefore not a nice-to-have, but a survival requirement for relevance outside the U.S.
Second, the EU’s regulatory regime is far stricter around both messaging and AI:
- GDPR makes conversational logs personal data by default. That forces Linq and its customers to think hard about retention, data minimisation and cross-border transfers.
- The Digital Services Act (DSA) and upcoming AI Act will likely require clear labelling of AI interactions, transparency around automated decision-making and strong user control — especially when AI agents are indistinguishable from human contacts in your phone.
- Under the Digital Markets Act (DMA), Apple narrowly avoided having iMessage classified as a “core platform service”, but the political pressure for interoperability and fair access to messaging channels is not going away. Any attempt to block third-party AI agents in Europe would attract regulatory scrutiny.
For European SMEs and startups, the opportunity is significant: imagine travel agencies, e-commerce shops or healthcare providers offering a WhatsApp-native AI concierge that speaks the local language, understands local regulations and integrates with existing back-office systems. A player like Linq could make that technically trivial — if it embraces European channels and compliance from day one.
6. Looking ahead
Over the next 12–24 months, several fault lines will determine whether Linq becomes critical infrastructure or just another clever middleware startup.
1. Platform politics.
Apple’s stance on third-party AI agents in iMessage is the biggest single risk. If the company follows Meta’s historical pattern and restricts automated accounts, Linq’s U.S. advantage shrinks overnight. Conversely, if Apple borrows from WeChat’s playbook and formalises “mini-apps” or agents inside Messages, Linq could either be a launch partner — or be sherlocked.
2. Channel expansion and depth.
Supporting WhatsApp Business, Telegram bots, Slack and email is table stakes. The differentiator will be how deeply Linq integrates: can it manage authentication, shared context across channels, human handoff, payments, compliance logging? The more of that it owns, the harder it becomes to rip out.
3. Verticalisation.
Generic APIs are powerful, but revenue often comes from opinionated, vertical solutions. Expect to see Linq (or its customers) lean into sectors like sales, customer support, logistics or healthcare, shipping templates and best practices for “agent-in-a-chat” workflows.
4. M&A pressure.
If Linq continues to post metrics like 295% net revenue retention and zero churn, it becomes an obvious acquisition target for cloud platforms (AWS, Google Cloud), CRM giants (Salesforce, HubSpot) or communications incumbents (Twilio, Sinch) that are racing to add AI-native capabilities.
Watch for three signals: first, when a major European or Latin American startup publicly standardises on messaging-native AI using a platform like Linq; second, when we see the first regulatory investigation into deceptive AI chat in consumer messaging; and third, whether Apple or Meta announce formal frameworks for third-party AI agents inside their flagship messaging apps.
7. The bottom line
Linq’s $20 million round is more than another AI funding headline; it’s a bet that the future of software looks less like an app grid and more like a contact list. If AI agents become just another conversation in iMessage, WhatsApp or Telegram, the companies that control the plumbing between models and messaging will wield outsized influence.
The real question for founders and product teams is simple: when your next AI product launches, will you spend months building an app — or will you make it a phone contact that users can text within seconds?
