--- title: "The software behind millions of Snapchat conversations" description: "An influencer marketing company whose business ran on conversations. I reverse engineered Snapchat's private API, built the bots that did the talking and a phone farm run by AI, and the console that ran 10,000+ Snapchat and 5,000+ Instagram accounts at once." url: /work/social-rise-studio markdown: /work/social-rise-studio.md case_study: true updated: 2026-10-13 --- # The software behind millions of Snapchat conversations Social Rise Studio · Horizon Beam · Dec 2024 to Jul 2026 > I built all of Social Rise Studio's technology, end to end, through Horizon Beam: bots that held about 3 million conversations on Snapchat in six months, a phone farm where AI drove every phone, and the software 150 virtual assistants worked in. | Fact sheet | | | --- | --- | | Client | Social Rise Studio, United States | | Role | Built all of its technology, end to end, and managed the virtual assistants who worked in it | | When | Dec 2024 to Jul 2026 | | Who else | Me, through Horizon Beam, on every system. A team of virtual assistants worked in the software I built, and I managed them. | | Stack | TypeScript, React 19, Vite, Express, MongoDB, Socket.IO, Browser extensions, AI, A phone farm | ## Headline numbers - **about 3 million** conversations on Snapchat, in six months - **10,000+** Snapchat accounts running at one time - **150** virtual assistants working in software I built ## The problem Social Rise Studio is an influencer marketing company, and its business ran on conversations: people talked to one by one, on Snapchat and Instagram, at a volume no team could type by hand. From December 2024 to July 2026 I built all of its technology through Horizon Beam. Snapchat doesn't give software a public way to hold a conversation. So before anything could be automated, I had to get software talking to Snapchat at all. And it was never only software. Thousands of accounts, a farm of phones and 150 virtual assistants had to run as one system, every day. ## Constraints - Snapchat has no public API for conversations, so everything ran on its private one, which I worked out myself. - The bots had to post, reply and hold a conversation the way a person does. - Thousands of Snapchat and Instagram accounts ran at the same time. - A large team of virtual assistants worked in the same system, so each person could only see the accounts and servers assigned to them. - A server can only carry so many accounts at once. ## Decisions 1. **Give every staff login only the accounts and servers assigned to it, with a super admin above them**, over one shared view where everyone saw everything, because with that many people in one system, staff could see each other's accounts and servers, and each of them should only see their own. 2. **Assign accounts to servers in bulk, by each server's capacity**, over placing them one at a time, because each server could only carry so many, and there were thousands of accounts. 3. **Build software to run the assistant team**, over managing the team by hand, because the team was large, and I was the one managing it. ## Snapchat: millions of conversations The centre of it was Snapchat. I built a Snapchat extension and the bots behind it: they could post, reply and hold a conversation the way a person does. Over six months they talked with about 3 million people. Every one of those had to answer what the other person actually said, and keep going. ## Reverse engineering Snapchat's private API Snapchat gives software no public way to do this. Its app talks to its servers over a private API with no documentation, so I worked it out myself and built everything else on top of it. At the time it felt close to impossible, and it's the part of this work I'm proudest of. How it works stays private. ## Instagram On Instagram I built an extension, the AI API behind it and an app. Same job as on Snapchat: post, reply, hold the conversation. It held 750 conversations. ## A phone farm run by AI We ran the entire Snapchat operation, and that included a phone farm. Every phone in it was driven by AI: we told it what needed doing, and it did it. ## Thousands of accounts at once At one time 10,000+ Snapchat accounts and 5,000+ Instagram accounts were running. That many accounts is an operations problem as much as a software one. So I built an operations console for it: every account, the server it ran on and its status, and who on the team owned it. Servers were filled by capacity, and the jobs that came up every day had bulk tools. It was one TypeScript app: React in the browser, Express and MongoDB on the server, one process serving both. ## Reddit, X and LinkedIn The same idea went to Reddit, X and LinkedIn. On Reddit it was an extension and a whole managed platform that did marketing for people: it found the leads, worked out what to post, posted it, talked with the people who answered and converted them. We built the same for X and for LinkedIn. ## Software for the assistant team Not everything was a bot. I managed 150 virtual assistants who worked alongside the software, for Social Rise Studio and companies like it. So I built the software they worked in. A super admin saw everything; every assistant saw only the accounts and servers assigned to them, and the server enforced that on every request, not just the screen. ## How it fits together The studio decided what needed doing. The operations console held every account, server and assistant, and the assistants worked in it through their own logins. The conversation AI did the talking through the extensions on Snapchat and Instagram. The phone farm took instructions and carried them out on its phones. The same pattern ran on Reddit, X and LinkedIn. ## The system The console, the conversation AI, the extensions, the phone farm and the platforms they talked to. - The studio (decides what needs doing) → Operations console (accounts, servers, roles) - Virtual assistants (each sees only their own) → Operations console (accounts, servers, roles): scoped logins - Operations console (accounts, servers, roles) → Servers (filled by capacity): assigns by capacity - Operations console (accounts, servers, roles) → MongoDB (operations data) - Servers (filled by capacity) → Browser extensions (Snapchat and Instagram) - Conversation AI (posts, replies, talks) → Browser extensions (Snapchat and Instagram): the talking - Browser extensions (Snapchat and Instagram) → Snapchat (through its private API) - Browser extensions (Snapchat and Instagram) → Instagram (an AI API and an app) - The studio (decides what needs doing) → Phone farm (AI drives every phone): what needs doing - Phone farm (AI drives every phone) → Snapchat (through its private API) - Conversation AI (posts, replies, talks) → Reddit, X, LinkedIn (find, post, talk, convert) ## Results - On Snapchat, about 3 million conversations in six months. On Instagram, 750. - 10,000+ Snapchat accounts and 5,000+ Instagram accounts running at one time, on one system. - 150 virtual assistants working in software I built, managed by me. - It ran from December 2024 to July 2026. ## The numbers | Metric | Before | After | How measured | | --- | --- | --- | --- | | Snapchat conversations, over six months | | about 3 million | My own figure, not audited | | Instagram conversations | | 750 | My own figure, not audited | | Snapchat accounts running at one time | | 10,000+ | My own figure, not audited | | Instagram accounts running at one time | | 5,000+ | My own figure, not audited | | Virtual assistants working in the software | | 150 | My own figure; I managed them | _The figures on this page are mine, from running it. They aren't audited._ _Social Rise Studio is named, and these figures are shown, at my own call. No account, handle, person, message or screen is shown, and how any of it worked stays private._ ## Contact - Email: hi@namanbuilt.com - LinkedIn: https://www.linkedin.com/in/naman-jain-hub Horizon Beam is taking on new projects.