Solution Overview & Summary Statement

Shared Lens serves as an intelligent, multi-source migration platform designed to streamline the complex process of transferring data from disparate systems into the Aras PLM environment. At its core, it acts as a robust engine for aggregating information, leveraging advanced data mapping techniques to ensure that source data from various repositories is accurately translated and aligned with the target schema required by Aras.

Furthermore, Shared Lens is purposefully designed to empower subject matter experts, ensuring they are at the center of addressing mapping challenges. By providing intuitive interfaces and transparent mapping logic, it enables these domain specialists to directly guide and resolve complexities, ensuring the data accurately reflects the business logic and standards they dictate throughout the migration.

Key Benefits of the Shared Lens Solution:

  • Accelerated Migration Timelines: Streamlines ingestion and mapping to significantly reduce project duration.

  • Improved Data Quality: Uses automated consistency checks to catch and address anomalies early.

  • Reduced Manual Errors: Limits the risk of data corruption or human error through automation and structured workflows.

  • Enhanced Team Collaboration: Provides transparent workflows that keep everyone aligned throughout the lifecycle.

  • Enterprise Scalability: Built to comfortably handle massive volumes of complex enterprise data from multiple legacy systems.

Operational Overview

Stage 1: Initial Import Activity

  • The process begins with the end user identifying the specific data sources and data types designated for migration. As part of the Shared Lens services engagement, this data is converted into an Adaptive Markup Language (AML) format. This AML file structure is what is ultimately imported into the Shared Lens environment.

  • Upon entering the system, a unique pedigree is established for every single tag-value item, identifying the exact source, the user who performed the action, and the specific date and time of ingestion. To ensure absolute data integrity, the system deliberately establishes this lineage and tracking pedigree first, rather than attempting to align or force the data to the target schema at this early stage.

Stage 2: Preliminary Mapping Exercise

  • During stage two, the imported data is evaluated by an AI engine to optimize the linkage between the source data and the target schema. Upon completing this automated process, some tag values will naturally remain unmapped and will require a level of disposition. This is where the domain subject matter experts step in. Based on their deep experience and operational understanding, they handle the process of evaluating and mapping these orphaned attributes. Accordingly, Shared Lens is explicitly designed to support multiple users, roles, and varied expertise to guarantee all data is properly reconciled.

Stage 3: Preliminary Mapping Validation

  • Once users believe all the data has been reconciled, stage three generates a preliminary mapping of the data to the target schema. This full mapping structure is entirely available for open review, allowing organizations to thoroughly evaluate, validate, and finalize the exact data footprint they want to bring over and manage within the Aras environment.

Stage 4: Final Import Operation

  • Once the organization confirms that the data has been properly and accurately mapped, they execute the final import into the Aras environment. This is an entirely automated process within Shared Lens. The system ensures that all data seamlessly maps to the target item types and attributes. Furthermore, any associated physical files are imported during this step, with their own specific item types and corresponding attributes created exactly as previously defined.

Spend Less Time Chasing Data and More Time Making Informed decisions. 

What It Does

  • Ingests multiple data sources
    Work with data across systems, spreadsheets, and shared repositories.

  • Supports staged processing and analysis
    Organize how data is reviewed, refined, and mapped over time—with AI helping structure and guide the workflow.

  • Enables collaborative data interpretation
    SMEs review, connect, and align data to target models, with AI assisting in highlighting patterns and inconsistencies.

  • Tracks issues and gaps
    Automatically generate and manage issues tied to decisions and data gaps—reducing manual tracking and follow-up.

How AI Is Applied

Shared Lens uses AI to augment—not replace—your team’s expertise:

  • Identify gaps and inconsistencies across large data sets

  • Surface decision points where alignment is required

  • Assist in organizing and structuring data for review and mapping

  • Generate and manage issues tied directly to data and decisions

  • Accelerate collaboration by reducing manual analysis and coordination

Typical Use Cases

  • Data migration and transformation initiatives
    A structured, AI-assisted alternative to traditional, manual approaches

  • Enterprise system programs (PLM, ERP, QMS)
    Align source data, target schemas, and stakeholders

  • Classification and data organization efforts
    Accelerate early-stage structuring and rationalization of data

  • Cross-functional decision management
    Capture and resolve decisions tied directly to underlying data

How it works

Example Use Case: Simplify PLM Migration with Shared Lens and Easily Collaboration, Validate, Migrate with Confidence

Getting Started

Shared Lens operates as a true Software-as-a-Service (SaaS) platform hosted in the cloud. The pricing structure is designed around flexibility, charging a fixed monthly infrastructure fee alongside a per-user fee to easily accommodate natural team scaling throughout the migration lifecycle:

  • Base Usage Fee: $1,000 per month for the dedicated cloud instance.

  • User License Fee: $250 per month for each user actively participating in the four-stage migration process.

Learn more