Transform retail workflows with collaborative data pipelines, AI-powered personalization, and compliant live apps. From demand forecasting to recommendation engines, accelerate commerce with reproducible environments and cost-efficient GPU computing.
Retail organizations struggle to democratize customer insights across teams. MINEO's data apps platform enables your data scientists to create interactive applications that merchandising and marketing teams can actually use.
Transform complex Python models into self-service tools for buyers, marketers, and operations teams - no coding required for end users.
Create collaborative retail workflows with automated compliance, real-time inventory tracking, and seamless integration with e-commerce platforms, POS systems, and customer data sources for streamlined operations.
Enable cross-functional retail teams to work together on demand forecasting, customer segmentation, and personalization systems with shared notebooks, version control, and real-time collaboration tools.
Transform commerce notebooks into production-ready Streamlit dashboards, Gradio recommendation interfaces, and FastAPI services with one-click deployment, maintaining retail compliance and audit trails.
Leverage high-performance GPU computing for recommendation engines, demand forecasting, and customer analytics while maintaining retail compliance, frozen environments for reproducibility, and cost-efficient variable pricing.
Real examples of scalable retail pipelines, GPU-accelerated personalization, and live commerce apps with compliance and cost-efficient computing
Build collaborative demand forecasting workflows with GPU acceleration. Teams analyze massive sales datasets, deploy predictive models, and maintain frozen environments for consistent forecasting at variable costs.
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Scale customer analytics with collaborative pipelines and GPU computing. Multi-team segmentation workflows, shared environments for insights validation, and live apps for targeted marketing.
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Transform pricing operations with collaborative optimization pipelines and GPU acceleration. Teams process competitive data, deploy dynamic pricing apps, and optimize costs with variable computing for complex calculations.
Scale personalization with collaborative recommendation pipelines and GPU acceleration. Multi-team workflows for recommendation systems, shared environments for model validation, and cost-efficient computing for real-time personalization.
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Transform inventory management with collaborative pipelines and GPU computing. Teams optimize supply chains, deploy predictive stock apps, and maintain reproducible environments for consistent inventory planning.
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Scale customer lifetime value analytics with collaborative pipelines and GPU acceleration. Cross-functional teams analyze customer journeys, deploy CLV models, and maintain frozen environments for consistent retention strategies.
Transform A/B testing with collaborative experimentation pipelines and GPU computing. Teams run complex experiments, deploy testing apps, and optimize costs with variable computing for large-scale statistical analysis.
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Scale visual search with collaborative computer vision pipelines and GPU acceleration. Teams build image similarity models, deploy visual search apps, and maintain reproducible environments for consistent product discovery.
Scale retail AI with collaborative development pipelines. Teams build and deploy retail LLMs with GPU acceleration, maintain compliance through frozen environments, and optimize costs with variable computing for conversational commerce.
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MINEO creates a collaborative environment where data scientists and retail professionals work together seamlessly
Transform notebooks into customer-facing apps without e-commerce complexity
Let MINEO handle UI, scaling, and retail integrations automatically
Get instant input from business users to refine retail models
Access sophisticated retail models through intuitive interfaces
Get customer and business explanations in plain language
Run scenarios and get answers without waiting for IT
Enable a collaborative retail culture where technical expertise and business insight drive exceptional customer experiences together.
See MINEO in action. Explore real data apps built with MINEO and get inspired by how the platform can be used to transform complex Python notebooks into interactive applications across different industries.
Explore All Data Apps
MINEO is trusted by data scientists, engineers, and organizations worldwide.
It is super powerful. You can create all the BI you need using Python directly as if it were a Jupyter Notebook but with a much better presentation. You can create super visual and useful panels using Python and present them as production panels to display your data.
Tech Lead, Data Truth
Great platform for working and collaborating with Python Notebooks
Operations Director
MINEO has the features of Power Bi and Google Colab, all in one. I have been working with MINEO for more than a year. I have been able to perfectly carry out both data analysis and visualisation projects, as well as more advanced data science projects.
Data Scientist, MIOTI
Great platform to build dashboards and data apps over Python Notebooks. MINEO Assistant is a truly game changer!
CTO, Perif.ai
Excellent platform combining Google Colab with great data visualization and analytics
Senior Deep Learning Scientist
An alternative to PowerBI and Google Colab combined into one unique tool.
Software designer and developer
GREAT Data Analytics and Data Visualization in an online collaborative platform!
Full Stack Engineer, Unlimiteck
Your All-in-One Tool for Data Science Projects. I have now been using MINEO for almost a year, and I can confidently say it has transformed the way I approach data science projects.
Data Scientist
Easy interface to create a dashboard with Python code (Pandas, Matplotlib, etc.). The distribution of modules is seamless, without the limitations of libraries like Dash.
Biomedical research engineer
Empower your entire retail organization with data apps that bridge the gap between data science and business decisions
