Computer Vision for Warehousing
Let’s build a custom computer vision development that will optimize your warehousing operations, improve inventory management, and help you transition into Industry 4.0.
What is computer vision for warehousing?
Computer vision is a set of techniques that let computers analyse images and videos automatically. The process can be distilled into three steps:
- Data gets captured with cameras, 3D scanners, thermovision or industrial sensors;
- It get processed by the system using classical image processing or machine learning (especially deep learning);
- The system makes decisions or they trigger human assistance (e.g. classifying a product as compliant or non-compliant).
Each computer vision solution developed by DAC.digital for warehousing environments helps operations managers address challenges across the storage and distribution process, such as inventory verification and package inspection to safety monitoring and shipment tracking.
What’s the purpose of computer vision in the warehouse?
Warehouse managers use computer vision to get a better understanding of what’s going on in their warehouse, automate processes, and work faster. Here are some examples of how computer vision is used in the warehouse and what you can do with it.
Visual proof to confirm items match orders
Vision systems recognize items picked for an order and compare them against digital order records to track orders before shipment.
Inventory tracking
Computer vision detects and tracks items on shelves or pallets and updates inventory counts, so managers can automate documenting and improve management.
Pose estimation
This application of computer vision identifies a worker’s body posture and movement. Read about one of our pose estimation projects that we can optimize for the warehouse purposes.
Pallet detection and monitoring
By using computer vision tasks such as object detection and object tracking, you can identify pallets and equip warehouse robots in detecting and transporting pallets.
Parcel identification
Computer vision can identify packages and read their labels. For this, you’ll need object detection and optical character recognition (OCR for short).
Receiving and shipping validation
Monitor goods as they enter or leave the warehouse and keep track of product type and quantity without the need for manual documentation.
Predictive maintenance
Train computer vision to monitor your equipment for the signs of wear and tear, and predict when machines require servicing.
Safety monitoring
Monitor what’s going on in your warehouse. Make sure there are no leaks of dangerous substances, people are safe and they’re wearing gear like helmets or gloves.
Why build custom computer vision for warehousing
Smart warehouse market is expected to grow at a CAGR of 14.22% from 2025 to 2034. Even though there’s a growing trend and many companies are building solutions that are tailored to warehouse needs, some warehouse managers cannot find an off-the-shelf solution and decide to develop their own systems when they face one or more of the challenges listed below.
- Quality requirements that off-the-shelf tools can’t address.
- Integration with warehouse software.
- Custom workflows and processes that need a unique approach.
Sounds like you? Tell us what you need computer vision for and we will help you figure out how to build a custom solution.
What skills to look for in an engineer who can build industrial computer vision?
Based on the summary of how computer vision is used in a warehouse automation, a skilled engineer in this setting should be able to configure and integrate hardware such as cameras, sensors, drones, and AI accelerators and make it compatible with warehouse IT infrastructure and edge computing systems.
They must bridge the gap between custom deep learning models and full-scale deployment, and build computer vision for tasks like quality control, pose estimation, object recognition, OCR, and drone inspections.
If you want to build your own team, we recommend you hire a computer vision expert who knows how to deploy the projects beyond R&D phase.
How to build warehouse computer vision
There are a set of steps that you need to take to integrate computer vision into your warehouse operations. At DAC.digital, we came up with our unique 3-step approach that delivers ROI-driven warehouse computer vision solutions. Here it is.
Step 1: Define scope and expectations
Clarify the warehouse challenges you want to solve, such as inventory tracking, pallet detection, or shipment validation. Align stakeholders on objectives, assess feasibility within your ecosystem, and create a preliminary roadmap. If you want expert help, we provide workshops as a standard part of our computer vision development service or as a standalone product. Read more about them here: Industrial AI Workshops.
Timeline: 1-3 business days + report generation.
Step 2: Develop a pilot project
Build a pilot computer vision system to validate feasibility and performance. Collect and annotate representative warehouse data (e.g., pallets, barcodes, shipments under real conditions), then train AI models to handle object detection, OCR, or anomaly detection. It’s a way of testing your solution before you commit to full development.
Timeline: 1-2 months depending on the project.
Step 3: Full-scale implementation
Expand from pilot to full warehouse deployment across receiving, packaging, and shipping points. Integrate with Warehouse Management Systems and edge devices, as well as set up data pipelines and monitoring.
Timeline: 2-4 months depending on the project.
How much does it cost to start?
While full deployment represents the largest investment, the process should begin with targeted workshops priced at 3000 EUR per day, and a custom pilot project to prevent unnecessary expenses before full commitment. Key cost drivers include the number of cameras and checkpoints, the complexity of CV models, integration with existing warehouse systems, and compliance with client’s requirements. For a final estimate, use the form below and let us ballpark your project.
Learn More About Us through Computer Vision-Related Case Studies
What else you might need from DAC.digital
Our Technology Stack
Machine Learning & AI
Scikit-Learn, OpenAI API, OpenMMLab, OpenVINO, Safetensors, SAM2, DINO, OpenCV, Open3D
MLOps
Weights and Biases, neptune.ai, SIGOPT, Optuna
Cloud & Data Platforms
Apache Kafka, Apache Spark, Snowflake, dbt, Argo Workflows, Matillion, Airflow, AWS Sagemaker
Data Analytics
Scikit-Learn, Polars, Prometheus, Grafana, PowerBI, Sweetviz, Seaborn
Explainable AI
LIME, ELI5, omniXAI
Data Management
PyTorch Lightning, MongoDB, Redis, MySQL, PostgreSQL, MS SQL Server, Talend, DWH & Data Lakes, Databricks, Azure Blob Storage, CVAT
Edge ML
Nvidia TAO, Edge Impulse, PyTorch mobile, Embedded systems integration
Get More Visibility Into Your Warehouse Process with Custom Computer Vision
Revolutionizing warehouse operations with computer vision and AI solutions is no longer reserved for enterprise-level companies. Let’s build a system that identifies bottlenecks, reduces labor costs, prevents errors, and helps you stay ahead in the fast-evolving technology trends of the warehousing industry.
Contact us!
Send us an email: [email protected]