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Custom Computer Vision ML Models Development

Reach new technological capabilities for your business with development of custom machine learning models. We create an optimal ML model, evaluating its accuracy to deliver a production-ready solution tailored to your specific business needs.

CV/ML models

At ByteAnt, we’ve been providing software development services since 2006. We can help you implement and build custom CV/ML models to automate business processes and gain your company productivity.
Based on machine learning algorithms, image analysis solutions can understand visual content and extract relevant information pertaining to image classification, object detection, image segmentation, pose estimation. By leveraging strong machine learning expertise, we handle all data-related processes, including data collection, model training, model deployment on cloud, edge or mobile.

Sports & Wellness

Want to take your sports app to the next level?

Whether your sport is fitness, yoga, dance or martial arts, an CV-powered automated coach will encourage your clients to train harder and harder.

Machine learning allows you to get the most out of the interaction with the client - you can determine how well the exercise was performed, count and record exercises and movements. CV-driven live advice on how good their workouts are by pointing smartphone camera at themselves.

Give your customers the flexibility to join your activities whenever and wherever they want.
You can create personal training plans for clients: exercises, number of runs and sequences. The results will be automatically written to the back end of your application.

Develop your specialty - add your own unique moves and poses, become special in your niche, without the extra cost of human trainers.

The most basic sports CV models:

  • Pose estimation
  • Pose classification


CV is especially useful in retail. Visual search helps customers search for products by using images - they can upload them or make a photo. Search engine powered by algorythm which trained with a lot of images. Customer can literally find the right match within seconds, check where it is available and what price is.

Using computer vision you can define the action that will be the trigger. For example, if a queue is noticed in your store, you will be notified that cashiers need to come.

Heat maps and retail analytics will help your business identify the hottest and most popular spots in the store, as well as your customer profile - vision computer can determine gender, age, and even separate into regular or new customers through constant model training.

Another examples CV/ML models in retail:

  • Client journey heat map
  • Distance control
  • Facial recognition
  • Retail analytics
  • Not wearing a mask
  • Presence of other objects
  • Queue management

Construction & Manufacturing

In construction and manufacturing, safety plays an important role.

Using CV models videosurveillance operators can deploy computer vision based models to detect abnormal activity or presence or absence of key actors or objects. Such apllication is deployed to the edge to be close with the data and is integrated with the rest of IT infrastructure for automatic and fast notifications.

Concise and consistent safety improvement through injury prevention not only benefits your workers but also the overall productivity, profitability, and efficiency of your business.

Models functions:

  • PPE detection
  • Risk zone monitoring
  • Pandemic control measures
  • Behaviour pose detection
  • Housekeeping
  • Vehicle controls
  • Construction progress tracking
  • Arrival of departure of specific cars or equipment
  • Counting of objects in specific zones
  • Quality control based on image data
  • Presence of other objects 

How does it work?


It allows you to deploy computer vision machine learning models to servers and hosting providers, such as Azure, AWS, DigitalOcean without any coding or shell level access.
It wraps machine learning model and exposes it via RESTful API.

The customer gets a possibility to do a Scan of object/image and get on the screen all information about it. You customize application based on custom data and insights, and identify good starting case with clear customer value.

Customer can deliver to host video or photo and get information about detect it object. It is an easy solution for business the No-code product that which is created as a result of integration.


Enables rapid deployment of Computer Vision Machine Learning models to edge devices such as Raspberry Pi, Google Coral, or NVidia Jetson. Edge devices makes possible analysis of video in near real time without the need of sending data to other servers.

Provides production grade boilerplate code which wraps the machine learning model
Connects the model with images or videos and provides HTTP trigger mechanism for integration
Supports both PUSH and PULL no-code deployment options thought web-based interface

Data sources:
- Photos
- Video files
- RTSP video stream
- Video stream from hardware



CV allows your employees to do higher-value tasks that technology can’t do, CV in turn handles tasks at a pace and scale that humans can’t catch. This efficient distribution improves the productivity of your workers by depriving them of monotonous and repetitive. It provides better quality of work and reduction of human error.


Computer vision is providing an appealing, entertaining, intuitive product for consumers to return to. Add this technology to your app and it will be successful and satisfying. Identify people, places, and objects of interest in images with greatest accuracy, speed, and efficiency for diverse applications across industries.


Your model is continuous improving. ML algorithms gain experience, they keep improving in accuracy and efficiency. This lets them make better decisions unique for your specialty. Solve novel & complex problems across various industries.

Our expertise across industries


Сomputer vision based models to detect abnormal activity or presence or absence of key actors or objects for ensuring work safety.


Visual search - trained model which reads images to identify color, shape, size and proportions, even text to identify brand and product names.


Detection, clustering and vizualization of human cells in the same cluster.
Extracting embeddings of detected cells with the help of encoder from pretrained convolution neural network.


Pose estimation and pose classification for sports applications, model can control how well the exercise was performed. Real-time detection of soccer ball, gates and goal events model for soccer analytics.


Pests detection - a specially trained model identified pests on the farm. This model is helping to improve the overall harvest quality and accuracy.

What our clients say

Our work in action


SentiFactory MLOps platform provides an easy to use solution to deploy your models to server and edge device targets without any coding.

  • Edge application template
  • Mobile application template
  • Server application template

Football game video production solution

A combined computer vision ML model deployed to an on premise setup, integrated with a PTZ camera. Camera is controlled by the software to follow the game play. Real time analysis of the camera video stream:

  • soccer ball detection on the field
  • gates detection
  • goal event detection

I want to develop several computer vision models for my business, but my case seems to be specific. What is the cost of model development? 

The price starts from $5K and depends on: 

  • Complexity and number of algorithms needed 
  • Dataset availability (already present or needs to be prepared) 
  • Inference (processing) requirements 

You mentioned that the model needs to be trained using collections of data. Do I need to collect and provide data to you? 

This is not required. Our team can use either publicly available datasets for your use case or use photos (videos) from real scenarios to prepare datasets. In the latter case (preferred) we will need the media assets from you. For decent results thousands of photos are needed, ideally under different conditions and view angles. They can be prepared from videos recorded by your cameras. 

I have a very individual case and my model is likely to require special precision and continuous improvement, in what ways do you improve the models? 

The models are improved by enriching datasets, re-training, and re-deployment. Datasets are enriched by gathering photos with false detections (false positives and false negatives), labeling them and re-training the models. Except that, models can be improved by gathering photos under different conditions that were not available on initial model development. For example, lighting, weather, year season etc. Also, datasets can be enriched by using photos from online available datasets or scraping. 

I have camera data and photos, but they are not labeled, can you help me with this? 

Yes, we do. Our team provides data labeling services for computer vision ML model training using photos collected online or in real time from your cameras. 

It would be nice for me to be able to process real-time data in order to send timely notifications to my workers. Can I implement a model that would work in real time? 

For real-time processing video we deploy computer vision models to edge devices such as Raspberry Pi, Google Coral, or NVidia Jetson. Edge devices enable analysis of video in near real time without the need of sending data to other servers. 

Start your project with us!
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Pärnu mnt 158/2-88, Kesklinna linnaosa,
11317 Tallinn, Harju maakond, Estonia,
Heroiv UPA St, 73в, office 34,
79041 Lviv, Ukraine,