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Fireside Chat, Conference Presentation

SQORUS & Oracle: How AI is transforming step by step our industries. Use cases by ONET

RAISE SummitCyril Grira, Geoffrey, Gaurit Champenois, Romain Guyettremotier
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  • Event Context: Oracle and Skorus celebrated 40 years of Oracle in France and 35 years of Skorus, highlighting a joint success story with client ONET Airport Services.

  • Key Stakeholders:

    • Cyril Grira: VP at Oracle France, leading Oracle Cloud Infrastructure (OCI).
    • Geoffrey (IT Director, Skorus): Manages 150 consultants, specializing in HR, finance, data, and IT digital transformation; Oracle partner for 20+ years.
    • Guillaume de Montessu: CIO of ONET, driving the vision to create the "Waze of the airport world" and innovate ground services.
    • ONET Airport Services: French family-owned company providing critical ground services (baggage, logistics, aircraft) for Air France at major hubs (CDG, Lyon, Toulouse).

  • Business Problem & Scale:

    • ONET manages 30 million bags annually for Air France connection flights at Charles de Gaulle.
    • Approximately 200,000 bags are currently lost yearly, incurring significant costs for re-routing and passenger compensation.
    • Operations involve 80 ground agents working 365 days a year (05:00–24:00) across complex logistics involving ULD containers, galleries, and carousels.

  • Strategic Objectives:

    • Improve productivity and operational performance by reducing lost luggage.
    • Transform manual, rigid procedures into real-time, data-driven decision-making.
    • Shift from "first-in-first-out" timing-based SLAs to value-based prioritization of critical baggage.

  • AI & Technology Implementation (OCI Ecosystem):

    • Core Infrastructure: Entire solution built on Oracle Cloud Infrastructure (OCI).
    • Database: Oracle Autonomous Database (23ai) serving as a unified transactional, application, and AI platform.
    • Development: Oracle APEX for rapid local application development (free with database) and React Native for mobile agent apps.
    • AI Services Integrated:
      • OCI Machine Learning: Predictive algorithms to forecast agent placement needs (galleries, repatriation, departure) and prioritize critical ULDs based on connection times.
      • OCI Vision: OCR for document scanning; anomaly detection on aircraft via agent-captured photos/videos before takeoff.
      • OCI Speech: Voice-command activation for tracking tasks (e.g., passenger onboarding, plane tours) similar to WhatsApp/ChatGPT interfaces.
      • Generative AI: Automated "GOM" (Standard Operating Procedures) query system where agents ask AI questions to retrieve specific operational instructions.
      • Natural Language Querying: 23ai allows direct natural language prompts to the database (e.g., "Which airport has the most connecting flights?"), generating SQL and results automatically.

  • Operational Results & Learnings:

    • Performance Gain: Operational performance improved immediately; luggage recovery increased by 25%.
    • Procedural Shift: High-performance recovery challenges existing SLAs based on rigid timing; necessitates renegotiating service agreements to value "saved bags" over strict "first-in-first-out" schedules.
    • Real-Time Requirement: OCR processing was initially comparable to human speed; algorithm optimization was required to achieve true real-time performance critical for baggage transfer.
    • Technical Scalability: Autonomous Database handles automatic index calculation and CPU scaling; development teams verify prompt-generated logic in lower environments before production deployment.

  • Future Roadmap:

    • AI-Driven Assignment: Transition from AI recommendations to AI-directed mission assignment, where an autonomous agent directly allocates tasks to employees without manual regulation.
    • Augmented Reality (AR):
      • Equip transport vehicles with visualization and communication systems.
      • Deploy AR interfaces on mobile phones and smart glasses (replacing legacy Google Glass concepts) to overlay critical baggage data and task instructions directly onto the agent's field of view.

  • Q&A Technical Clarification:

    • Load Management: The Autonomous Database manages indexing and performance scaling automatically.
    • Development Safety: Prompt-to-sql capabilities are tested in development environments; critical production systems utilize additional service layers to ensure stability.