Computer vision enables systems to identify objects on images or videos and take relevant actions. Using the most recent neural networks like GAN, we create reliable computer vision applications that allow our clients to automate work processes.
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We get in touch with you and find out the project details — what exactly you need and how we can meet the challenge. Then we offer several solutions based on your time and budget expectations.
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It’s important to do business analysis at the start of any project: without it you won’t know if users need your product. We’ll study the market, competitors and potential users to help turn your idea into a successful product. After the research we’ll define the project scope and provide you with the quote.
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Training a neural network requires a lot of representative images. During tech analysis we find out if we have enough data. If it’s not enough or we need images of better quality — we can find or create the required dataset.
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We create mind maps and wireframes to work through the basic logic of the app. Then we ‘dress up’ the screens with colors, fonts and animations — this approach helps us create beautiful and user-friendly interfaces.
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We develop computer vision systems of any complexity for any business. Our development process is divided into sprints: this way we can show you intermediate results and keep you in the loop.
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Combining manual and automated testing, we make sure that your product works properly on all devices. We also run load tests to determine how much your computer vision AI system can handle.
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Of course, the work doesn’t end once the computer vision system is developed. We provide post-release support to all of our clients — all terms and details will be described in the SLA document.
We carefully choose tech specialists. Our experts have Master’s and PhD degrees in mathematics, specialize in different development areas and some of them have 20+ years of experience.
Computer vision uses AI to train systems to see, interpret and understand visual data. Using digital images and videos and deep learning models, computers can identify and classify objects, and then react to what they “see”.
Computer vision companies require a lot of images — about 1000 for each category. One of the first things that we do is evaluate the quality and quantity of the client’s images. If there aren’t enough images or they are of poor quality, we can help the client collect additional data. Find a required dataset, create a system that collects such data or request volunteers to make the needed pictures.
If needed, we can sign an NDA document. This way you’ll be sure that we won’t steal your idea or disclose sensitive information.
We need about a month to develop an MVP model of such a system. The more features and requirements — the more time it takes.
To calculate the most accurate cost of our services, we multiply the hours needed for the project by the hourly rate of each specialist on the team. If you want to get a quote — feel free to contact us. Just fill in the form below 😉
Brivian works based on the Time and Material model. It means that you pay for the working hours of our specialists and materials used for the project.
Every project team includes a project manager who will be responsible for communication and make sure that the team meets the deadlines.
We apply the most recent technologies, such as generative adversarial networks (GAN). They appeared not a long time ago, and most computer vision companies still use old technologies and don’t maximize their results. We do because GAN networks show a higher output.
Usually, we create computer vision systems using Python. When developing systems that need fast object recognition, we code in C/C++ — for better optimization. Here’s what we use most often:
Languages: Python, C/C++, Go
Libraries: TensorFlow, Keras, OpenCV, PyTorch, SciPy, Pandas, NumPy, Spark, Chainer