Outsourcing for machine
learning and data
analytics projects
Application of technologies in business
Object recognition in photos
Evaluation of in store display shelving
Approximate record matching and fuzzy lookup
Technological process optimisation to reduce manufacturing defects
Churn rate prediction
Automation of marketing reports
Object recognition in photos
We offer solutions for object recognition and classification in photos or video.
Our technologies can be used for content moderation and classification, image tagging, identification of manufacturing defects etc.
Evaluation of in store display shelving
We can analyse the display of products in the stores through photographs. The system will identify and evaluate the range of products and collect statistics on specific brands or SKUs present on the shelves.
Approximate record matching and fuzzy lookup
We are able to locate and consolidate fuzzily duplicated records to simplify the work of editors and analysts.
Technological process optimisation to reduce manufacturing defects
At a production facility where a complex technological process is used, results are dependant on the temperature, composition, and properties of the components as well as beginning and end times of the various steps within the production cycle.

In cooperation with production engineers, we will implement a system focused on the monitoring of the technological process, which provides real-time recommendations on adjustments in the production parameters to minimise defective articles.
Churn rate prediction
If you provide subscription-based services, or users regularly return for purchases, we can collect the data and build a model that predicts the probability of users canceling their subscription. These results will enable you to process this target segment directly leading to a reduction in customer churn rates.
Automation of marketing reports
Marketing departments often spend much time collecting data from different sources, such as databases, CRM tools, Google Analytics and Excel files.
Our systems will assist in curating all of the data into one database, normalize it, restructure it to an analytical form, and develop interactive reports featuring valuable business metrics.
Our process
Build a simple model
We implement a simplified model for solving the problem (using PyTorch or Keras), which allows for full analysis to be undertaken without the risks associated with implementing unproven technical solutions.
The stage takes place at our facilities.
Improve the quality of the model
We iteratively enhance the quality of the model while generating and testing hypotheses that will help to improve the effectiveness of training. We ultimately select the optimal model architecture, the most effective method of preparing the data, and the training process.
We document the work on each hypothesis to preserve the knowledge gained and to guide informed decisions.
This stage can occur at either our facility or yours.
Launch full-scale operation
We migrate the model into Tensorflow, prepare the production servers, and set up processes for quality control and regular updates of the model incorporating new data.
When solutions require working with big data, we will deploy the Hadoop stack (HDFS, Hive, Spark) either at your facility or through Amazon AWS.
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