Chinmay Amte, known as Excel Pro, has 78,000 followers on LinkedIn. Over several years he built a body of work: 750+ posts on business, mindset, and professional growth. Thousands of comments. A community that engaged with everything he wrote.
None of it was findable on Google. None of it was his.
A LinkedIn post lives for three days in the algorithm. After that, it exists only for people who specifically visit his profile. Someone searching for “how to structure a sales conversation” or “how to handle rejection in business” would never find Chinmay’s answers, even if he’d written the best version of that answer on LinkedIn six months ago.
That was problem one. Problem two was in the comments. The same questions kept appearing under different posts. Chinmay was answering them personally, one at a time, every day.
What We Built
We approached this as two connected problems that needed two connected solutions.
First, the content migration. We built an automation pipeline that pulled every post from his LinkedIn profile, classified each one into meaningful topic categories using AI, and published them to a personal website with full search and filtering. The migration itself took one day. The result was a searchable content library, indexed by Google, that surfaces his thinking to anyone looking for it, not just his existing followers. As a linkedin automation agency that has run this process before, the tooling was already refined.
Second, the chatbot. With 750+ posts now structured and accessible, we had everything needed to train an AI assistant on Chinmay’s actual knowledge. The chatbot answers audience questions by drawing exclusively from what Chinmay has written and said, in his voice, with references to the specific posts where he covered the topic.
The repetitive comment questions stopped needing him. His content started reaching people who had never heard of him.
The Outcome
His website now ranks for long-tail queries in his niche. Posts he wrote two years ago are finding new audiences through search. The chatbot handles the volume of repetitive questions his growing audience brings.
You can read about each piece separately: how the migration worked and how the chatbot was trained on his voice. Together, they’re what a complete content infrastructure actually looks like.
Talk to us on WhatsApp to discuss what we’d build for your content library.