To most people, writing is hard. In expert domains, AI doesn't solve the difficulty. We found another way.Plot twist: I started my career in math and computer science. I also did research in Machine Learning, back when only academics thought it was cool. When deciding I was neither a developer nor an academic, I thought: “Well, this wasn’t very useful.”Instead, I got into financial writing for investment banks and asset managers.But everything changed once I realised I could use Natural Language Processing to supercharge the writing process: first, I could uncover the patterns in what investors enjoy reading and adapt accordingly. Then, I could automate parts of the writing process itself. Finally, I could educate companies how to use these tools to cut times and increase output.Thus, I gathered a small team and founded FinText. (visit us at fintext.io)We do three simple things:◼️ One, we benchmark content, providing data on what wins investors' trust and attention.◼️ Two, we offer software tools that make creating expert financial writing easy.◼️ Three, we provide training on using tech to improve marketing processes.The following buzzword-infested part caters to the LinkedIn algorithm:I've built a startup that provides tools to benchmark and create written marketing in expert domains. I've focused on selling those tools to financial services companies - primarily investment managers. For core functionality, I build in Python. I've done lots of NLP (sentiment tagging, text-data extraction, named entity recognition, natural language generation, text summarisation and text analytics). I also work with large language models using the Hugging Face platform. For web apps, I taught myself front-end dev. I build with Node, React, Redux (and a potpourri of related tech).