PapAI, the next generation artificial intelligence platform

Make data processing and analysis accessible to all users and quickly deploy predictive models to impact your business strategy.

Transform your Operations with Data Science

A collaborative and scalable platform for end-to-end management of your data projects.
Collect, cleanse, analyze and deploy your predictive models

Data Collection Protocols

Import relational databases (postgreSQL, mySQL, Oracle, MicrosoftSQL), upload CVS and Excel files, and insert APIs from a custom Python script.

An intuitive interface to quickly and easily integrate your data at any time during the prototyping of your predictive model.

Data Cleaning

The platform’s agile ETL will speed up massive data transfers to enhance your productivity outputs. The calculation engines are distributed without any configuration on your part.

For your own personalized use and visualization, you have a great latitude to customize your code design via Python.

Visualization

Create your own analyses and choose from the different vizualization models offered (Statistics, Histograms of numerical and categorical data…). You can also view 2D, 3D and geographical plots. Compare several models for a better vizualisation and easily access the visualization models of your collaborators.

Our powerful algorithms recognize different types of models and detect missing values and duplicates.

Deployment

Powerful Machine Learning engineering will enable you to swiftly and easily deploy your predictive models throughout your pipelines : Feature Selection, Element Coding & Scaling and Data Separation.

Pipeline designs enable you to compare performance and use in large algorithms : regression, clustering, time series.

Your models’ outputs would clearly access the accuracy in the selected model to render insightful input data relevance and results’ utility.

They trust us

SNCF : Asbestos detection

"Today, when the solution tells us that there is no asbestos on a car, we can trust it 100%! It has never been wrong. And when it reports asbestos, the error rate is less than 1 percent."
Patrick Munsch
Head of Wagon Maintenance & Engineering at SNCF Voyageurs

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