Computer vision replicates the capabilities of human vision by teaching machines to process, analyze and make decisions based on visual data. The technology relies on a combination of machine learning, deep learning and neural networks to improve its accuracy and capabilities. 

Utilizing the diverse AI Proving Ground lab environments and following this methodology, WWT tailors computer vision solutions that meet your organization's unique needs.

AI Proving Ground environments

The AI Proving Ground contains multiple pre-defined multi-OEM architectures and almost limitless custom configurations. This enables building, testing, training and validation of all the components of enterprise AI solutions.

Explore pre-defined lab environments

WWT's methodology

Discovery phase

• Client consultation: We begin by understanding your specific needs and the context in which the computer vision solution will be used. This involves detailed discussions to identify the most compelling scenarios relevant to your industry and audience.
• Scenario planning: Based on the consultation, we develop potential use cases. For example, one scenario might focus on real-time quality control in manufacturing. The system needs to provide immediate alerts if any defects are detected in the products. Another example may be data aggregation in a retail environment. In that case, the system collects data on customer behavior and store traffic throughout the day, and generates reports and insights that help store managers make informed decisions about staffing, inventory and store layout.

Solution design

• Technology selection: Leveraging advanced platforms, we define the infrastructure architecture and design the computer vision solution to include features like machine learning, deep learning and neural networks. This allows the solution to process and analyze visual data effectively. We consider latency and bandwidth requirements when selecting technology. For instance, real-time alerts require low latency and on-premises hardware, while data aggregation can be managed with higher latency and cloud-based solutions.
• Customization: We tailor the solution's functionalities to align with your brand identity and operational requirements. This includes conducting a build-versus-buy analysis to determine whether to develop the solution in-house or leverage existing solutions from partners, considering factors such as cost, time and intellectual property ownership.

Prototyping and proof of concept

• Initial development: We create a prototype for you to review. This prototype serves as a preliminary version to gather feedback and make necessary adjustments.
• Client feedback: You are presented with the prototype for detailed feedback. This iterative process helps the final version meet your requirements and expectations.

Innovative solutions and enhancements

• Creative problem-solving: Throughout the development process, we address any technical challenges that may arise. We revisit latency and bandwidth considerations to ensure the solution meets initial requirements and make necessary design adjustments.
• Additional functionality: We enhance the prototype with the functionality and features that you request so the completed solution meets all your specific needs.

Rigorous testing and troubleshooting

• Quality assurance: We conduct extensive testing to confirm the solution's accuracy and performance, ensuring the overall user experience is polished.
• Collaborative effort: Our development team works collaboratively to identify and resolve any issues, ensuring the solution performs flawlessly.

Deployment and training

• System architecture: After successful testing, the solution is deployed in your environment—in the cloud, at the edge or on-premises—with a robust system architecture.
• Training and documentation: We provide comprehensive training and documentation, including video and written instructions, to help your team effectively operate and demonstrate your computer vision solution's capabilities.