AI Development Services

Leverage the Power of Computer Vision to Transform Your Organization

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Introducing a New Era of Computer Vision Services

At Wovenware, we're pioneering the next generation of computer vision technologies. Leverage our decades of expertise to transform the way you see the digital and physical worlds.

In a rapidly evolving digital landscape, computer vision services stand as a beacon of the transformative potential of AI. Wovenware, with over two decades of expertise, crafts computer vision solutions harnessing the power of machine learning to detect, classify and derive insights from images. Dive into our offerings to discover how we create solutions custom-designed for you. From solutions that gather insights from satellite imagery, to those that help to diagnose medical conditions, Wovenware has built a reputation as an AI leader, tailoring innovative solutions for forward-thinking organizations

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Helping Maxar Create the  World’s Largest Satellite Imagery dataset

Accurately labeling millions of high-res images requires trained annotators with specialized toolsets. Wovenware worked with Maxar Technologies to enhance its proprietary Deep Workbench tool with more advanced annotation, project management and quality features. Leveraging our deep computer vision expertise, Wovenware created over 10,000 high-quality training datasets and tagged more than 2,000,000 images to build computer vision models that can automatically detect and classify objects based on the Maxar xView dataset.

Other client success stories


A Track Record of Excellence in Computer Vision

Choose Wovenware for your artificial intelligence development needs. With more than 20 years of experience, and backed by Maxar, a leading space technology company, we deliver unparalleled quality and innovation.

Didn't find the exact computer vision service you're seeking?

Wovenware specializes in crafting bespoke solutions. Reach out and let's shape your vision together.

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Computer Vision Applications

Wovenware's Computer Vision Services Development Process

From prototype labs to design sprints, our development process is designed to align with your business objectives and technological requirements.

• Discuss specific needs related to computer vision services.
• Understand the scope of facial recognition, object detection, or any other tailored solution required.

• Conceptualize the architecture for image classification, video analytics, and other computer vision functionalities.
• Draft blueprints incorporating machine learning and deep learning methodologies.

• Craft solutions, from augmented reality modules to optical character recognition systems.
• Integrate scene understanding and depth perception capabilities as per client requirements.

• Conduct rigorous product inspection to ensure software quality.
• Utilize traffic monitoring and medical image analysis test cases for comprehensive evaluation.

• Implement the developed computer vision solution into the client's ecosystem.
• Ensure seamless functioning of features, from motion tracking to 3D reconstruction.

• Provide tutorials on the utilization of robotics vision, natural language processing, and other features.
• Offer continuous support to ensure predictive maintenance and fraud detection services operate optimally.

• Gather feedback on the solution created and deployed, augmented reality modules, or any specific solution provided.
• Iterate and refine based on real-world performance and client feedback.


Wovenware's Scrum-Based Computer
Vision Services Development Process

Our nearshore software development team employs Scrum methodology, ensuring a flexible, collaborative, and high-quality production process.

Technologies employed

Stay ahead of the curve with our extensive expertise in software development tools and technologies, ranging from machine learning to cloud computing.









Darknet (Yolo)

JavaScript (with TensorFlow.js)



React with react-webcam

HTML5 Canvas

WebRTC for real-time video

TensorFlow Lite

CoreML (for iOS)

Android NN API

OpenCV for Android


ARKit (for augmented reality applications on iOS)

ARCore (for augmented reality applications on Android)

OpenCV with Python or C++

TensorFlow with GPU acceleration

Qt for GUI-based applications

Electron for cross-platform applications

OpenGL for rendering and visualization








Microsoft SQL Server

Oracle Database



Amazon RDS

Google Cloud SQL

Microsoft Azure SQL Database

Amazon DynamoDB

Google Cloud Firestore

Azure Cosmos DB

Firebase Realtime Database

Amazon Redshift


Apache Spark

Apache Kafka

Apache Flink

Apache HBase




AWS (Amazon Web Services)

Azure (Microsoft)

Google Cloud Platform

IBM Cloud






Travis CI


GitLab CI/CD

GitHub Actions





Travis CI


GitLab CI/CD

GitHub Actions



Bitbucket Pipelines

Cost Variables

We offer various pricing models that align with your budget and project complexity.
Contact us for a customized quote and cost breakdown.

Complexity of the desired computer vision application: This refers to the level of intricacy and sophistication needed in the computer vision system you are developing or using.

Depth and specificity of facial recognition requirements: Describes how detailed and specific the demands are for facial recognition capabilities within your project.

Describes how detailed and specific the demands are for facial recognition capabilities within your project.

Measures the quantity and complexity of features related to detecting objects in images or video.

Indicates the level of detail required when integrating optical character recognition (OCR) technology into the application.

Describes how long and how complex the processing of video data is within the project.

Refers to the quantity and scale of motion tracking features incorporated into the system.

Measures the extent to which the system can comprehend and analyze the content of scenes or environments.

Describes the level of precision needed for depth perception tasks.

Indicates how intricate the tasks related to 3D reconstruction are within the project.

Refers to the inclusion of features related to natural language processing (NLP) in the system.

Describes the degree of customization required for machine learning models in use.

Measures the extent and variety of deep learning algorithms employed in the project.

Indicates how comprehensive the features for inspecting products are within the application.

Describes the level of detail and precision required for quality control processes.

Measures the intricacy involved in integrating fraud detection capabilities.

Refers to the demands for predictive maintenance features within the system.

Describes the scope and range of functions related to traffic monitoring.

Indicates the level of precision and depth needed for medical image analysis.

Refers to the specifications and demands for vision-related features in self-driving car technology.

Describes the integration of vision capabilities into robotics systems and the associated complexity.

Measures the intricacies and complexities of augmented reality features.

Refers to the expected timeframe and schedule for the project.

Indicates how many rounds of modifications or revisions may be necessary.

Describes the expenses related to hardware and infrastructure for the project.

Refers to the costs associated with licensing third-party tools or platforms.

Indicates the needs for training and support once the system is deployed.


Related Sub-Services

From legacy application modernization to artificial intelligence services, we provide a spectrum of related services to complement your computer vision project.