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AI Architecture for Deliverable Automation

Rail industry – Document AI & deliverable automation

Data and AI architecture to automate deliverable production, quality control and traceability.

Traceable deliverables

From source information to produced documents, with human validation where it binds

Project Details

Client

Alstom

Sector

Rail industry – Document AI & deliverable automation

Year

2025

Key Technologies

LLMDocument AIAPIsData modeling

Mission

AI Tech Lead & Data Architect - Deliverable Automation

Document AI & deliverable automation

Hybrid assignment, France. English.

Scoping of a data and AI architecture to automate the preparation and production of technical deliverables. Mapping of sources, document formats and validation steps to build a coherent processing chain. Design of AI-assisted extraction, structuring and generation components, integrated into document production processes. Technical coordination between business needs, application development and data quality requirements.

Contexte & Environnement

Industrial environment: heterogeneous technical documents, multiple frameworks and need for consistency across deliverable versions. Gradual automation of repetitive tasks, while keeping human validation for binding content. Modular architecture allowing processing components to be reused across several document families.

Team

AI Tech Lead & Data Architect

Environment

Hybrid, France – modular document pipelines with LLM extraction and generation

Objectifs Cles

1Standardize input data, deliverable templates and control rules to limit manual rework.

2Ensure traceability between source information, transformations and produced documents.

3Define the interface contracts and validation tests required for reliable integration.

4Document architecture choices and maintenance procedures to ease handover to the teams.

Technologies & Infrastructure

LLMInformation extractionContextual searchTemplate-based generationData modelingAPIsDocument pipelinesAutomated testsVersioning

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