Automating creating Tidy Data

application badge
Created by team Munich-AI-Agents on August 21, 2023

We believe that the cause why many data science projects fail is that are error-prone and long winding data cleaning processes. We are building the tool - tidyAI - for data scientists that automates data preprocessing and cleaning. tidyAI is built on top of an AI agent, which can adapt to the particular challenges present in the data file. The planner detects the mistakes present in the data that might prevent a future analysis or visualization and generates a list of transformations to apply. The executor takes the top transformation and applies it to the dataset. We do not want to take over the job of a data scientist and analyst, we want to free him up from the grunt work, the work he hates to do, so the data scientists can focus on the work that excites them and that provides value: the analysis.

Category tags:

"it is a dream come true for every data scientist. it is great work with perfect application of technology, and perfect presentation. the idea has been in minds, but now it is reality, it will save a lot of time for data scentist, hence for tech companies. it is exceptional work, as a data scientist, i struggle a lot in this phase. now it occurs with one click. thanks"


Walaa Nasr Elghitany

Lablab Head Judge

"This team seems to tick the majority of the submission guidelines apart from exceeding the time limit for video presentations was way over the mark. I liked the idea so much because as an ML Engineer sometimes it's frustrating to clean datasets. Good work, The demo app was wonderful, and looking forward to what this app achieves in the future. "


Muhammad Inaamullah

ML Engineer

"Sometimes we have an immense amount of data in the ML, DL, and data science fields, and our whole project depends on this information. It's time time-consuming process to evict the unnecessary data. This will definitely be helpful to every person related to these fields. It reduces the time consumption and is more accurate."


Muhammad Mubashir Hassan