What challenges did Akkodis face before AI implementation?

Manual measurement validation from thousands of complex technical drawings is time-consuming and prone to inconsistencies. Global engineering teams need rapid, reliable access to precise technical insights across multiple revisions and versions. The system must support high concurrency, scalability, and efficient handling of large datasets. Accuracy, speed, and resilience are critical to support global operations and engineering precision.

What was the impact of the AI solution?

Achieved precision that meets or exceeds customer thresholds for measurement accuracy. Reduced query response times from minutes to seconds for near real-time engineering access. Enabled consistent and reliable technical data extraction globally to enhance engineering decisions. The solution significantly lowered manual validation effort and improved data quality for drawing analysis.

Source

Evidence: Low40/100

Akkodis Builds Scalable AI Technical Drawing Analysis for Global Automotive Manufacturer with AWS

Use case typeDocument automationUpdated Jun 13, 2026

Akkodis partnered with a global Italian automotive manufacturer to automate technical drawing measurement extraction and validation using scalable AI on AWS. The solution integrates Amazon SageMaker, Amazon Bedrock, Amazon Textract, and Amazon Rekognition in a serverless pipeline to extract, interpret, and validate engineering data. It provides near real-time access for global engineering teams, ensuring accuracy and scalability with multi-region deployment and secure authentication via Amazon Cognito. The AI-driven automation reduces manual effort, speeds decision-making, and maintains high precision across large datasets of complex technical drawings.

Organization: Akkodis
Industry: Automotive
Location: Italy
Published: January 2026

Reported outcomes

Strategic outcomes

New product / capabilityBuilt scalable AI drawing analysis pipelineSpeed & agilityEnabled near real-time engineering accessBetter decisions & insightImproved engineering decisions with reliable dataCost efficiencyReduced manual validation effort

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: Akkodis
Provider: AWS
Maturity: Unknown
Linked source: Akkodis

No explicit deployment-stage evidence found.

Customer identity supportedSource describes one deploymentMaturity evidence evaluated

Primary read

Use case focus

Showing 3 of 3

1AI-Powered Document Analysis
2Large Scale OCR
3Engineering Automation

Manual measurement validation from thousands of complex technical drawings is time-consuming and prone to inconsistencies.
Global engineering teams need rapid, reliable access to precise technical insights across multiple revisions and versions.
The system must support high concurrency, scalability, and efficient handling of large datasets.
Accuracy, speed, and resilience are critical to support global operations and engineering precision.

Developed a serverless scalable pipeline using multiple AWS AI/ML services: Amazon SageMaker IDE, Amazon Bedrock for LLM API, Amazon Textract and Rekognition for OCR and visual data extraction.
Implemented secure SSO authentication with Amazon Cognito and integrated scalable API endpoints with Lambda and API Gateway.
The solution processes large volumes of technical drawings efficiently and supports multi-region deployment for resilience.
The AI pipeline detects inconsistencies and supports concurrent requests to enable near real-time measurement delivery and engineering insight.

Technologies

Amazon SageMaker Amazon Bedrock Amazon Textract Amazon Rekognition Amazon Cognito AWS Lambda Amazon DynamoDB Amazon API Gateway

Achieved precision that meets or exceeds customer thresholds for measurement accuracy.
Reduced query response times from minutes to seconds for near real-time engineering access.
Enabled consistent and reliable technical data extraction globally to enhance engineering decisions.
The solution significantly lowered manual validation effort and improved data quality for drawing analysis.

Architecture

The architecture uses Amazon SageMaker IDE for development, invokes Amazon Bedrock LLM API for query processing, extracts data using Amazon Textract and Rekognition, and manages scalable serverless functions with Lambda, API Gateway, and DynamoDB, secured by Amazon Cognito, deployed multi-region for resilience.

Sources & evidence1

Evidence: Low40/100Evidence strength