Freja Warehouse Digital Twin Case Study: Real-Time 3D Visualization and AI Optimization

Project Overview

About the project

Warehouse operations are becoming more complex as facilities grow in size and handle larger volumes of data. That said, many teams still rely on separate systems and manual processes, which makes it harder to maintain visibility and respond quickly to changes.

Read our digital twin warehouse case study to see how TechVision helped the client address these challenges using modern technologies.

Warehouse Digital Twin Case Study: Real-Time 3D Visualization and AI Optimization

Location:

Sweden

Industry:

Warehouse

Platform:

Web

Team Size:

8 members

Project duration:

18 months

Technologies & tools:

Unity

React

.Net

PostgreSQL

AWS

Lambda

RDS

OpenAI API

SyncFusion

Stripe

Business Needs

Challenges

The client wanted to move beyond traditional warehouse management tools by introducing a next-generation warehouse management solution that combines traditional enterprise functionality with a real-time 3D digital twin. The idea was to combine standard warehouse management functionality with a real-time 3D digital twin, giving teams a more intuitive way to understand what's happening across the facility and make faster, more informed decisions.

To bring this vision to life, we had to address the following technical challenges:

/01

Integrating a high-performance 3D engine into a standard enterprise application

/02

Ensuring smooth interaction between the user interface and the 3D digital twin environment

/03

Handling large-scale warehouse data while maintaining system responsiveness and low latency

/04

Connecting to multiple existing data sources through a flexible and extensible architecture

/05

Designing a consistent user experience that combines 3D visualization with familiar interface elements

/06

Supporting advanced warehouse management and data analytics

We support. We improve.

Our Solutions

To support the client’s vision, TechVision designed a scalable architecture that combines real-time data processing, 3D visualization, and warehouse management functionality in a single environment. The focus was on making the system responsive, easy to integrate, and capable of handling large, dynamic warehouse operations without performance issues.

A real-time synchronization framework connects the 3D digital twin with the underlying application logic. It allows changes in warehouse operations to be reflected instantly in the visual environment, while user interactions within the 3D model feed back into the system without delays. As a result, teams can work with up-to-date data and interact with it in a more intuitive way.

To ensure stable performance at scale, we introduced optimized data models, as well as streaming, indexing, and caching mechanisms, allowing the platform to handle large volumes of warehouse data with low latency. This makes it possible to monitor complex facilities in real time without slowing down the system.

Our team developed robust integration layers that connect the platform with existing warehouse management systems and enterprise tools to support smoother data exchange and system interoperability. On the frontend, we refined the rendering pipeline to create a responsive user experience.

The final interface combines analytical dashboards with the 3D digital twin, so users can move between data views and visual representations without switching tools.

To further improve efficiency, the platform incorporates AI warehouse optimization features that support dynamic slotting for better inventory placement, optimized pick-path generation to streamline warehouse workflows, and real-time recommendations based on operational data. Together, these capabilities help teams reduce manual effort and respond more quickly to changing conditions.

that received

Result

Freja combines warehouse management, real-time 3D warehouse visualization, and advanced analytics in a single environment. It provides a real-time 3D view of the warehouse, enabling teams to monitor operations and respond to changes on the floor more quickly.

Freja’s AI-driven optimization features streamline warehouse management, suggesting teams better inventory placement and optimizing picking routes, which results in more efficient day-to-day operations. At the same time, built-in analytics give managers clear insights into performance, helping them track key metrics and identify areas for improvement.

The platform was designed to integrate with existing enterprise systems, so organizations can adopt it without reworking their entire infrastructure.

Freja enables companies to move away from manual, spreadsheet-based tracking and adopt a more advanced, data-driven approach to warehouse management. Better use of space and more efficient picking processes lead to reduced costs, while access to real-time data and intelligent recommendations allows teams to make faster, more informed decisions.

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This 3D warehouse visualization case study shows how combining visualization, analytics, and AI tools can help optimize warehouse processes at scale. If you're exploring the potential of AI and 3D digital twin technologies in enterprise warehouse management, TechVision can help. Get in touch to discuss your needs, and we'll propose a solution to take your logistics and warehouse operations to the next level.

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Freja Warehouse Digital Twin Case Study: Real-Time 3D Visualization and AI Optimization

About the project

Challenges

To bring this vision to life, we had to address the following technical challenges:

Our Solutions

Result

Planning a Similar Solution?

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