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Related image for Amazon Bedrock

How msg Enhanced HR Transformation with Amazon Bedrock

ByteTrending by ByteTrending
September 17, 2025
in Review, Tech
Reading Time: 3 mins read
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This post is co-written with Stefan Walter from msg.

With over 10,000 experts in 34 countries, msg stands as both an independent software vendor and a system integrator, particularly strong within highly regulated industries thanks to more than 40 years of domain-specific experience. A key offering is msg.ProfileMap, a Software as a Service (SaaS) solution designed for skill and competency management. It’s an AWS Partner qualified software available on the AWS Marketplace, currently supporting more than 7,500 users. HR and strategy departments utilize msg.ProfileMap for project staffing and workforce transformation initiatives. Ultimately, this solution provides a centralized view of skills and competencies, enabling organizations to map their workforce’s capabilities, identify skill gaps, and implement targeted development strategies, which supports effective project execution and better alignment of talent with roles.

In this post, we’ll explore how msg automated data harmonization for msg.ProfileMap, leveraging Amazon Bedrock to power large language model (LLM)-driven data enrichment workflows. This resulted in higher accuracy in HR concept matching, reduced manual workload, and improved alignment with compliance requirements under the EU AI Act and GDPR.

The Challenge of Fragmented HR Data

Modern HR departments face increasing pressure to leverage data for informed decision-making. However, workforce information frequently resides in disparate systems—legacy databases, spreadsheets, Word documents, and PDFs—each presenting its own format and terminology. This inconsistency creates significant challenges; leading to manual inefficiencies, inaccurate insights, and difficulties aligning talent with strategic goals. For example, a skills database might use different terms for the same skill set as an applicant tracking system.

The Impact of Disparate Data Sources

Without a centralized and harmonized view of workforce data, organizations struggle to effectively match candidates to roles, identify internal mobility opportunities, conduct thorough skills gap analyses, and plan future workforce development initiatives. Furthermore, it becomes incredibly difficult to measure the effectiveness of training programs or accurately forecast future staffing needs.

Leveraging msg.ProfileMap & Amazon Bedrock for Data Harmonization

msg.ProfileMap addresses this challenge with a modular architecture specifically designed for IT workforce scenarios. The solution extracts data from various sources and formats, transforming them into structured information. Crucially, at the heart of the harmonization engine lies Amazon Bedrock, powering LLM-driven data enrichment workflows that greatly enhance the process.

Enterprise HR system architecture with ProfileMap centrally connecting four key modules for comprehensive workforce management
Architecture overview of the solution leveraging Amazon Bedrock.

How Amazon Bedrock Enhances Data Accuracy

The harmonization process utilizes a hybrid approach, combining vector-based semantic similarity with traditional string matching. Amazon Bedrock’s LLMs play a crucial role in semantically enriching data and improving the accuracy of concept alignment across different sources. This allows msg.ProfileMap to identify subtle nuances and resolve inconsistencies even when descriptions vary significantly—a significant improvement over traditional keyword searches.

Key Benefits & Regulatory Alignment

The integration of Amazon Bedrock into msg.ProfileMap delivers several key benefits, contributing to a more streamlined and compliant HR process.

  • Improved Accuracy: LLM-powered enrichment significantly enhances the accuracy of HR concept matching, reducing errors and improving data reliability.
  • Reduced Manual Workload: Automation minimizes manual effort required for data harmonization, freeing up HR professionals to focus on strategic initiatives.
  • Enhanced Compliance: The solution helps organizations adhere to regulations like the EU AI Act and GDPR by ensuring responsible and transparent use of AI in workforce management; therefore, promoting ethical data handling practices.

By leveraging Amazon Bedrock, msg provides a powerful and scalable solution for HR data harmonization, enabling organizations to unlock the full potential of their workforce with increased efficiency.

Conclusion: The Future of Workforce Management

msg’s collaboration with AWS demonstrates how innovative solutions can address critical challenges in HR. By automating data harmonization using Amazon Bedrock, msg.ProfileMap not only streamlines workflows but also empowers organizations to make more informed decisions and build a future-ready workforce. The combination of domain expertise and cutting-edge AI technology positions msg as a leader in the evolving landscape of talent management.


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