A PLM platform based on AI for small and medium enterprises






Decrease in operational cost


This project was developed for a Chicago-based client that offers end-to-end product development services. They needed software that would help them optimize the process. Through constant communication with the client and by implementing regression testing, we were able to add new features without compromising the system’s functionality. Now the client has successfully deployed this cloud-based PLM software at ten of their clients. The faster time-to-market has reduced costs substantially.


Product Conceptualization, Rapid Application Development


Angular.js, Node.js, Neo4j, Flowable, Spring Boot, PostgreSQL


Chicago, USA


The client is a provider from Chicago and needed a solid PLM software as an SEM solution to streamline product and service end-to-end processes. This posed a challenge as there were reactions being received from different end-users. Such feedback entailed a constant change of requirements, and the team had to work long hours to deliver quality while meeting deadlines.

The goal was to deliver highly efficient software that would allow for flexibility.

Technical Challenges

The client’s platform was built with advanced technology and was cloud-agnostic. In addition to the lack of documentation, this presented a huge challenge. The team also had to change their working hours to adapt to the users’ time zone and assure seamless communication.

The main objectives were:

  • Develop a highly functioning and fully customizable solution
  • High quality for every release
  • Manage the application lifecycle amid short-release cycles
  • Keep thorough process documentation

TechVariable focused on the following:

  • CAT file management
  • Check-in and check-out process optimization
  • Managing MVVM
  • Measurements
  • Process control


TechVariable chose a knowledge management approach to tackle the project’s challenges. The team kept close contact with the client to provide functionality and deliver several test cases. Thanks to the automated regression testing implemented by the developers, they were able to add features without compromising the overall functionality.

The team and resources were organized to handle these responsibilities as follows:

  • One technical lead
  • Two front-end developers
  • Two back-end developers
  • One QA

The team built a GUI-based codeless configuration module to extend existing data configuration or add new definitions easily. The system uses machine-learning algorithms to work with new datasets. This improves data analytics considerably for the end users while developing new products and implementing innovations.

Modules implemented

Graphical Display of Bill of Materials

There is the option of creating a table of the BoM and a graphical representation of various nodes. Users can click on any node to view its properties and perform CRUD operations on it.


TechVariable developed a system secure enough to enable various tenants to run applications on its platform. The design allowed granular access control and data segregation.

Modeler & Instance Pages

Users can add attributes to products and define relationships between these attributes on the modeler page, which results in schema generation in the graph database. Likewise, they can create types, instances, and attributes on the instance page and define their relationships and properties.

BoM Formulation

Users can customize a structure for its BoM and integrate it with the instance page so that different instances of types get captured in BoM. The solution allows documents with BoM information across stages to be attached for auditing purposes.

BPMN (Business Process Model and Notation) Integration

Users can diagram the workflow with TechVariable’s workflow orchestration tool. We introduced a cloning feature to compare similar products during product versioning. BPMN’s flowable engine that generates a workflow schema was incorporated into the modeler pages. In the instance page, the workflow schema is instantiated and attached to any type of structure. The workflow includes triggers and approval processes.

Elastic Search

The team implemented the elastic search for documents, structures, attributes, relationships, and types. It included fuzzy search and phonetic search. Users can search for shapes in different formats (JPEG, PNG, or CAD) and even draw doodles to search for similar shapes. TechVariable enabled ETL to pull out documents attached to any type or instance from one database to another and experiment with it, such as changes in resolution, color, or design.

High Level Design Architecture

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We at TechVariable do acknowledge that one size will not fit all. Hence, we work in collaboration with you to identify, analyze & then develop a solution that fulfills your needs. Either we will define the functional scope of your project to estimate the timeline and budget or you can create your own agile team from among our resources.
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The Result

  • Faster time-to-market
  • Cost reduction
  • Successful implementation of over ten enterprises
  • Creation of the first PLM entirely in the cloud at that time
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