AI-Assisted Multilingual PIM in Manufacturing & Electrical Engineering
Overview of Our Client
Our client was a global manufacturer in the electrical and cable industry, supplying power cables, industrial wiring systems and electrical components for construction, infrastructure, energy and industrial automation projects. The company operated worldwide and distributed products in dozens of markets, each with its own regulatory, language, and documentation requirements.
Their product portfolio included thousands of SKUs with highly detailed technical specifications. Every product had to be supplied with correct, compliant and up-to-date documentation, including installation instructions, safety notices and technical data sheets, in 24 languages.
Challenge
The client was confronted with several challenges that required a custom enterprise software development approach, caused by the size, complexity, and the need to comply with various regulations:
- The products were characterized by hundreds of electrical, mechanical, environmental, and regulatory attributes.
- Technical product data and documentation needed to be identical and consistent in up to 24 languages.
- Manuals consisted of structured data, free text, tables, symbols, and so on.
- Manual translation, validation, and review brought about delays, inconsistencies, and high operational costs.
- Inaccuracies or outdated information in manuals caused faulty installations, safety hazards, and non-compliance with regulations.
Main Goals
To resolve the identified challenges, our PIM development services focused on the following goals:
- Create a single source of truth (SSOT) for multilingual product data and documentation.
- Apply AI-assisted workflows to decrease translation and review efforts.
- Implement deterministic, rule-based validation of content completeness and consistency.
- Enforce the ability to create product instructions based on templates.
- Automate documentation generation using asynchronous pipelines.
- Make sure that only validated and human-approved content is allowed to be distributed to downstream systems.
Project Overview
We developed and implemented an enterprise-level PIM solution centered on multilingual data management and automated documentation workflows. The system centralized structured product attributes, multilingual content, layouts, and tables, while artificial intelligence-powered services provided support for translation, consistency checking, and automatic content draft generation.
One of the key architectural principles was the automation of processes involving large volumes of content, without blocking editorial or approval processes. Translation, verification, and instruction generation were performed asynchronously using event-driven pipelines, ensuring the completeness and approval of all exported content.
- Region: Global
- Industry: Electrical Engineering, Cables & Wiring Systems
- Timeline: 18 months
Solution
We delivered a scalable, AI-assisted PIM platform adjusted to electrical engineering manufacturers operating across multiple markets. The solution combined structured product modeling, multilingual content management, deterministic validation rules, and AI-assisted automation, while keeping final control firmly in human hands.
The system was deployed in a containerized, cloud-ready environment and integrated with the client’s ERP, PLM, CMS, and e-commerce platforms.
Key Features
- Centralized management of complex product data with hundreds of structured attributes covering electrical, mechanical, safety, and compliance parameters.
- Language-aware data model supporting up to 24 parallel locales with full versioning and audit trails.
- Rule-based validation enforcing mandatory attributes, formats, and market-specific requirements before publication.
- AI-powered translation of product descriptions, warnings, and instruction content with terminology control and human-in-the-loop review.
- AI-assisted detection of inconsistencies and conflicts across languages.
- Template-based authoring of product instructions using reusable blocks and dynamic placeholders linked to validated PIM data.
- AI-assisted generation of draft instruction narratives with conditional logic for market- or configuration-specific variants.
- Asynchronous, event-driven processing of translation, validation, and document generation to support non-blocking editorial workflows.
User Workflow
- Product Data Management: Engineers maintain structured technical parameters in the PIM, while rule-based validation ensures completeness.
- AI-Assisted Translation & Review: AI services generate translation drafts, and editors focus on review and approval of regulated or flagged content.
- Template Authoring: Technical writers define instruction templates using structured blocks and dynamic placeholders.
- Validation & Draft Generation: Rule-based validation and AI-assisted checks run automatically, followed by draft instruction generation.
- Approval & Distribution: Only content that has passed all validations and required human approvals is exported to ERP, PLM, CMS, or eCommerce systems.
Deployment & Roadmap
The solution was deployed in a scalable Kubernetes-based environment and integrated into the client’s enterprise landscape.
- The first phase delivered the core PIM and multilingual data model.
- The second phase introduced AI-assisted translation and validation workflows.
- The third phase implemented instruction draft generation and asynchronous pipelines.
- Planned extensions included market-specific regulatory rule sets, expanded use of generative AI in PIM driven by editor feedback, and customer- or project-specific instruction variants.
Technology Stack
In order to allow for a large-scale multilingual content management, an AI-assisted workflow, and integration with enterprise systems, we chose the following technology stack:
Backend
- Java
- Spring Boot
Frontend/UI
- React
Database
- PostgreSQL
AI Services
- Large Language Models (LLMs)
Async Processing
- Message queues, event-driven background workers
Document Engine
- Template-based layout and table rendering
Integration
- REST APIs
- ERP
- PLM
- CMS
- e-commerce
Deployment
- Docker
- Kubernetes
- CI/CD pipelines
Security
- Role-based access
- SSO
- Audit logging
Core Team
- Project Manager: Coordinated stakeholders and delivery milestones.
- Solution Architect: Came up with the AI-assisted PIM architecture and asynchronous pipelines.
- 3 Full-Stack Engineers: Were in charge of backend services, integrations, AI workflows, and document generation.
- Frontend Engineer: Developed template editors, translation, and review interfaces.
- QA Engineer: Checked the multilingual consistency, AI-supported outputs, and document accuracy.
Results
The introduction of the AI-assisted multilingual product information management resulted in quite a few quantifiable improvements in cost-effectiveness, quality, and compliance for the client’s global product documentation processes. The main achievements were:
- Up to 65% reduction in time required to create and update product instructions.
- Significant decrease in translation and documentation costs.
- Consistent documentation quality across all supported languages.
- Faster time-to-market for new and updated products.
- Higher confidence in documentation quality due to enforced validation and approval workflows.