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The Agentic OS for Retail Decisions,made in Montréal.

Backed by and in production at ALDO Group. Founded by Fatih Nayebi, author of Foundations of Agentic AI for Retail.

  • Montréal

    Where OODARIS is designed and built

  • ALDO Group

    Backer and customer

  • MFP and OTB

    In production at ALDO Group

  • 2nd edition

    Foundations of Agentic AI for Retail

Where OODARIS comes from

Built in retail: the people behind OODARIS were building AI inside ALDO Group before the company existed.

Proudly Canadian. Fièrement canadien.

Made in Montréal, Canada.Fait à Montréal, au Canada.

  1. Before OODARIS

    Years in AI, and one gap in retail

    Fatih spent years building AI products and putting them into production. In retail he kept meeting the same gap: merchants, planners and allocators spend a lot of their time getting to a decision, across spreadsheets, handoffs and static rules, before they can make it.

  2. ALDO Group2022–2025

    AI inside a retailer

    As VP of Data & AI at ALDO Group, Fatih built AI for the retailer's own decisions, from inventory optimization to assortment planning.

  3. McGill UniversitySince 2019

    Teaching how agentic AI is built

    He teaches at McGill, where students learn to design, build and run agentic AI systems.

  4. 2025

    Foundations of Agentic AI for Retail

    The ideas behind OODARIS are written up in Fatih's book. A second edition followed in January 2026.

    About the book
  5. OODARIS AI2025

    A company to close the gap

    Fatih founded OODARIS AI in Montréal to close that gap, with funding from ALDO Group, which is also a customer.

  6. The team

    A team from ALDO Group

    He brought a team from ALDO Group, some of them his former students at McGill. At ALDO they had built markdown optimization and order fulfillment optimization, which still run in production there. OODARIS rebuilt both from scratch on its own platform.

  7. Today

    In production at ALDO Group

    Merchandise financial planning and open-to-buy run in production at ALDO Group, across its four brands. All five decisions are available to new clients.

    Read the ALDO Group story

Mission

Turn retail data into decisions, every day. OODARIS watches the business overnight, explains what moved and proposes the fix; by default, its owner approves before anything is written back.

Vision

Every retail decision made with AI, from the season plan to the last markdown: less waste, more value, and the right product in front of every customer.

The team

The team building OODARIS spans agentic AI systems, operations research, data science, product and engineering.

We're hiring in Montréal and across Canada.

See open roles
  • Fatih Nayebi

    Fatih Nayebi

    Founder & CEO

    • Agentic AI systems
    • AI research
    • Machine learning
    • Design & architecture
    • Retail technology

    Fatih founded OODARIS and leads the company. He wrote Foundations of Agentic AI for Retail.

    He is an Assistant Professor at McGill University, where he teaches Designing & Building Agentic AI Systems, Deep Learning, Data Science, and Machine Learning in Production.

    He has worked with global retailers on AI research and its implementation.

  • Arnav Gupta

    Arnav Gupta

    AI Product Manager

    Arnav leads product vision and platform strategy at OODARIS.

    • Agentic AI
    • Retail planning
    • Product strategy
  • Allen Yang

    Allen Yang

    Full Stack Engineer

    Allen builds web applications end to end, from the interface to the AI integration.

    He works in MVC architecture and keeps the code easy to maintain.

    • Frontend
    • Backend
    • AI integration
  • Florian Denu

    Florian Denu

    Senior Full Stack Engineer

    Frontend and mobile developer with about a decade of experience on finance, weather, entertainment and medical products.

    He focuses on fast, responsive interfaces for complex workflows.

    • Frontend
    • Mobile
    • Performance
    • Product craft
    • User experience
  • Philippe St-Aubin

    Philippe St-Aubin

    AI Engineer

    PhD in industrial engineering and applied mathematics.

    Philippe builds agents that combine simulation, operations research and machine learning.

    • Operations research
    • Machine learning
    • Simulation
    • Digital twin
    • Agentic systems
  • Adrian Alarcon

    Adrian Alarcon

    Data Scientist

    Adrian designs production machine learning systems for retail decisions.

    His background is demand forecasting for large retail operations.

    • Artificial intelligence
    • Demand forecasting
    • Machine learning
    • Agentic AI
    • Data engineering
  • Arial Huang

    Arial Huang

    Data Scientist

    Master of Management in Analytics from McGill. Arial works on machine learning, demand forecasting and agentic AI for retail.

    • Machine learning
    • Agentic AI
    • Optimization
    • Demand forecasting
    • Foundation models

See OODARIS on one of your decisions

In a demo we follow one decision through OODARIS: what it checked overnight, what it proposed, who approved it and what it wrote back. A pilot reaches a first live cycle in 8–12 weeks.

  • +4–8%

    Gross-margin dollars

  • −8–12pp

    Discount depth

  • +1–3pp

    Margin rate

  • 8–12 wks

    To a first live cycle

Ranges measured in pilots and in production at ALDO Group, against an agreed control.