Data Collection
Data Cleaning
Data Visualization
AI & Deployment
Explainability & Interpretability
Data Collection
Import relational databases (postgreSQL, mySQL, Oracle, MicrosoftSQL), upload CSV and Excel files, and insert APIs from a custom Python script.
Data Cleaning
The AI 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.
Data 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.
AI & Deployment
In papAI, powerful Machine Learning engineering will enable you to swiftly and easily deploy your predictive models throughout your pipelines: Feature Selection, Element Coding and scaling, and Data Separation.
Explainability & Interpretability
papAI offers a high degree of explicability of results thanks to its counter factual and feature impact functionality.
Tailored AI for Healthcare's Data Scientists and Experts Needs
Of Explainability Rate, Offering Clarity and Trust in AI-driven Insights in the healthcare sector
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Healthcare Experts Benefits
With papAI, business experts are not simply recipients of the results of data science but become active participants in the process. They can take part in data cleansing, visualize data using intuitive visual tools, and participate in the creation and optimization of models.
Business experts can explore, share and manage datasets using papAI’s integrated data catalog. papAI without replicating data acts as an audit tool on all available data, wherever it is actually stored, and helps to make business sense of it.
papAI offers various explainable AI features, such as feature contribution analysis, sub-population analysis, and Shapley values. These tools can help business experts understand the decisions made by machine learning models and make informed decisions.
Data Scientists Benefits
Data scientists can build, orchestrate and optimize data pipelines from a No-Code graphical user interface, to accelerate and simplify the process of data preparation and analysis + data lineage, data governance, and automation.
All the tasks generated by users through no-code operations generate Spark tasks. These tasks are then automatically orchestrated on the integrated Spark cluster for optimal load balancing. The underlying infrastructure is self-managed and highly scalable. (Kubernetes).
papAI offers robust MLOps capabilities, enabling users to automatically deploy machine learning models in production, monitor them for quality and availability, and quickly retrain and redeploy them.
Hours Saved for Each Data Scientist Environment/Month
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The AI Platform Built for Your Industry
Clinical Decision Accuracy
Enhancing precision in medical diagnoses and treatments
Drug Discovery Speed
Accelerating pharmaceutical research and development processes
Patient Data Security
Safeguarding sensitive healthcare information with robust AI
Operational Efficiency
Streamlining hospital functions for cost-effectiveness and resource optimization
Medical Image Analysis
Rapid, accurate analysis of medical images for diagnostics.
High explainability power
Understanding the results of algorithms clearly and transparently
Visualization and Reporting
Gain actionable insights through intuitive data visualization
Real-time Monitoring
Detect and respond to churn at the moment
Speed up the journey from data collection to swift AI-driven decision-making
Discover how papAI streamlines AI project deployment in the hospital sector by accelerating diagnostic accuracy, improving patient care, optimizing resource allocation, and enhancing operational efficiency.
Discover how papAI expedites AI project deployment in the pharmaceutical sector by accelerating drug discovery, streamlining clinical trials, optimizing supply chain management, and enhancing quality control.
How do we ensure our client's success?
"With papAI Solution, we have a tool for caregivers to improve patient safety by providing accurate and efficient assistance in managing their health."
Benoist Alexandre Chief Engineer in charge of Clinical Engineering Development
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AI-powered churn prediction systems have been shown to reduce churn costs by up to 80%.
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