Hi Product Hunt, Abe from Akkio here, joined by my co-founders and team. Two years ago, we launched Akkio on Product Hunt and made #1 Product of the Day. We’re also the creators of Product Wars 2, where makers and hunters can monitor daily launches on Product Hunt. We can’t thank our community enough for the feedback and support you provided - your input has helped shape the product as we have continued to build it out! Today, we’re launching our newest feature: Chat Data Prep. Since we launched in 2021, we’ve continued to iterate and improve the product based on customer feedback. One of the biggest issues customers have is preparing their data because it’s time-consuming and complicated. Enter: Chat Data Prep. The fastest and easiest way to prepare your data for ML predictions. A few key points about the Chat Data Prep feature: All you need to do is upload your data, type your request in simple language, and we use NLP to interpret your request. In seconds, your data is transformed. No coding or SQL is needed. Some common use-cases include reformatting dates, merging columns, removing outliers, and many, many more. With Chat Data Prep, the transformation possibilities are endless! The capabilities should be particularly useful for Data Analysts and Excel super users. Akkio is free to try - no credit card needed - so feel free to play around with the feature. Most of all we are looking for feedback! We can predict the future (given the right data) but we can’t read your minds - so please do not pull any punches :) The Akkio team and I are here to answer any questions. If you’re curious, here’s a little backstory on Akkio: We have collectively spent our careers building technology companies, and they all had one thing in common - they had massive amounts of data but were bad at using it to improve business performance (and not for lack of trying, rather for lack of tooling). Machine learning is the most powerful technology for business since the internet. But almost no companies are leveraging it across their operations. Even cutting-edge tech startups find themselves in the data dark age. We tried various solutions, but in the end, we just wanted a self-serve ML platform that we could use every day. So we built it 🚀