The AI startup Photon is so sure that agents will eventually come to replace mobile apps that it held a funeral for the latter — yes, a real funeral in a church, with speeches and everything. Photon, which helps developers build agents that work over iMessage and WhatsApp, now has $4.5 million in seed funding to develop its products. The raise comes after the company signed up over 40,000 developers grew its revenue 10x in just four months, it says.
Photon co-founder and CEO Daniel Tian said the “app funeral,” held in San Francisco on September 17, was also a developer day for the startup, featuring panels from Vercel, Stripe, and OpenAI. It also included an actual coffin for app icons.
The move to host an app funeral was obviously somewhat tongue-in-cheek, but Tian believes the app era is coming to an end. “Honestly, it’s going to take a while, but I think, directionally, it’s inevitable,” he said of the shift from apps to agents.
The thesis behind the startup, as you may have guessed, is that users no longer want to install new apps. Instead, they want access to agents that work through the messaging apps they already use, like iMessage and WhatsApp.
Meta’s Muse, whose app has soared to No. 1 on the app stores, is putting that theory to the test. But even if Muse comes to dominate the consumer AI space, Tian sees a market for serving developers who want their applications to work over messaging services. That’s why Photon is offering a package of tools, including a unified API, an extensible channel framework, a command-line interface (CLI), and an observability suite. Combined, they allow developers to build and operate an agent experience that works over iMessage, WhatsApp, Telegram, SMS or RCS, email, voice, and more.
The idea for Photon emerged from the time co-founders Tian and Ryan Zhu, the CTO, spent building consumer apps as students, often at hackathons. Every time they finished a new app, they hit the same bottleneck: getting people to discover it. By building an agent that worked within iMessage, they realized they could reach people through an app those people already use every day: Apple’s Messages.
Tian, for instance, had built a bot that would text his friends back as him over iMessage. When he and Zhu made the technology openall in. Tian dropped out of UPenn’s M&T program, and Zhu left high school, later becoming a visiting student at MIT’s Media Lab
This April, the founders decided to create a managed platform and sell access to its 99.95% uptime, which is much higher than what you’d get if you were just running the open- 2 Type II and HIPAA-compliant, which opens the door to healthcare agent use cases
To date, the startup’s platform has attracted over 40,000 developer sign-ups and now includes paying clients. (Any usage beyond 10 users requires moving out of the free tier to one of the three paid tiers, we’re told.) The company isn’t sharing revenue figures but said that, in addition to the 10x revenue growth, it’s seeing less than 3% churn, and its messaging volume has grown by 5x in the last month alone.
Customers using Photon include Corgi Insurance; social introductions app Boardy; Gen Z dating platform Ditto; business banking platform Rho; finance AI assistant Fliptexts; AI email client Slashy; and others building agents for fintech, consumer AI, and other vertical use cases.
Photon’s technology integration partners also include companies such as like Vercel (Eve and ChatSDK) and Nous Research, whose Hermes agent uses Photon as its default iMessage layer. Photon is also the layer under Tencent’s QClaw and NanoClaw. Plus, Photon has seen framework and infra integrations across LangChain, Mastra, Convex, Render, Railway, and Telnyx, among others.
Vercel is also one of Photon’s new backers. The startup’s seed round was co-led by Gradient and A* with participation from Vercel, HongShan, Z Fellows, Llama Ventures, Karman, and other angel investors.
Across both the hosted and open- estimated
While today, Photon focuses on agents connecting with humans, Tian believes there’s potential to grow into an expanding market that involves connecting agents to other agents.
“I think, in the future, agents will be able to find you the agent that can do the right things — so it’s going to be the A-to-A communication layer,” Tian said. For instance, if a person was chatting with their AI assistant making travel plans, the agent could pull in other agents when needed, like a flight-booking agent or hotel-booking agent. “It’s been pretty powerful to observe the whole A-to-A-to-P [agent-to-agent-to-person] space,” he added.
