Can virality be turned into an analyzable and reproducible process? This is the premise behind Posty, a platform that uses artificial intelligence to identify what content performs on social media and automate the entire downstream workflow: from analysis and creation to publishing and continuous improvement. The application of this methodology has already allowed its cofounder, Judit Català, to grow her social media following by more than a million in just six months, while the project has surpassed €300,000 in revenue (roughly $320,000) and more than 600 clients in the first month after launch.
Currently, the company is focusing its efforts on consolidating the team, strengthening user support and expanding its technological infrastructure, with the objective of ensuring that the platform can scale with the user base and enter a new expansion phase.
Posty starts from a simple idea: the content that captures attention on social networks shares certain patterns that can be identified and analyzed. But the platform goes beyond detecting trends: it researches viral content in each user’s sector, analyzes why it worked, and uses that learning to generate original content, tailored to their goals and identity.
From this analysis, Posty uses the knowledge it gains about each user to create content that preserves their own voice and style. The platform includes a space where it stores the user’s content and references to learn their identity and use it in new pieces, avoiding results that take on the generic AI-generated tone. It also enables mass content creation, adapted to the needs of each account, and publishing directly to multiple social networks.
Detect, Analyze, Create, and Improve
One of Posty’s main features is that it does not merely generate content from scratch via AI. Its offering covers the entire cycle of social media content creation and management.
First, the platform conducts a search for viral content, looking for posts that are performing well in each user’s specific sector. From there, it analyzes their patterns to identify which elements explain their performance and uses that knowledge as a starting point to generate new ideas and content.
The next step is to tailor that learning to each user. Posty knows their voice, their content and their identity, so the generated pieces seek to preserve their personality and avoid the generic AI-generated feel.
This combination between trend analysis and knowledge of the user allows generating original content from what is already proving successful.
The platform also supports mass content creation, from scripts and copy to images, videos and carousels, and publishing it directly on the different social networks. In this way, the process that traditionally involves researching trends, analyzing competitors, developing ideas, producing the assets and scheduling posts is centralized in a single tool.
The process does not end with posting. Posty analyzes the results of each account (views, interactions, likes and comments) and shows which posts are performing best, so users can identify their most effective content and reuse those learnings in future pieces. The platform also stores the contents and references that the user decides to keep, and takes them into account when generating new content.
Currently, Posty integrates the leading AI models on the market, such as OpenAI’s GPT, Anthropic’s Claude, Google’s Gemini, Meta’s Llama and xAI’s Grok, along with Nano Banana Pro and GPT Image 2 for image generation, and Seedance for video. The difference from using any one of those models alone lies in what you can feed them: you only need to paste the link to an Instagram Reel, a TikTok or a YouTube video, or upload a PDF or document, and the platform sees it, transcribes it, and sends it to the AI of the user’s choice, together with everything it already knows about the account. Working with multiple providers lets you use the model that best responds to each task, without relying on a single one.
