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Machine learning and artificial intelligence

Create a smart app with machine learning (ML) to implement a greater degree of process automation, quickly react to market changes with accurate predictions, and get a lasting advantage over competitors.

  • Initiate new business models with computer vision, natural language processing, and speech recognition.

  • Handle multi-dimensional issues with non-traditional approaches based on improved analytics.

  • Speed up security risk discovery with integrated machine learning of patterns in your datasets.

  • Optimize labor costs with the help of robotic process automation and error-free documentation management.

ML- and AI-powered solutions

AI-driven forecasting

  • Collect and process a wide range of data including historical data, customer demand information, market data, currencies, and news content.
  • Build predictions with supervised ML, unsupervised ML, autoregression models, and more.

AI content analysis

  • Benefit from ML and AI services such as natural language processing, optical character recognition, text preprocessing and evaluation, spam filters, document clustering, and linguistic research.
  • Turn images, videos, and audio content into data sources and get trend labels as an output for further predictions.

Portfolio optimization

  • Build fast and self-improving algorithms to solve the combinatorial optimization problem.
  • Solve other real-life optimization problems with advanced tools such as genetic algorithms, simulated annealing, stochastic local search, and reinforcement learning agents.

Customer segmentation

  • Use all your data to create advanced customer segments and cohorts.
  • Use customer segments for building segment-specific forecasts, discovering customer behavior trends, planning targeted marketing, and launching new features.

Fraud detection

  • Implement an AI-based anti-fraud system strengthened by ML.
  • Discover and prevent email phishing, credit card and payment fraud, identity theft, document forgery, fake account identification, form jacking, account takeovers, and more.

Data mining

  • Build a data warehouse to structure your data for analytics and decision-making.
  • Use diverse techniques for data mining including association analysis, regression analysis, and classification and predictions.

Need a solution that’s not listed above? Contact us and learn what we can offer to meet your ML and AI app development needs.

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Who can benefit from ML and AI integrations?

AI- and ML-based software solutions can significantly increase value and efficiency for businesses in a range of industries. Below are just some of the possible benefits.


  • Optimize payment processes

  • Interpret medical images while minimizing errors

  • Create drug discovery solutions

  • Use AI systems that automatically learn for patient engagement


  • Automate fraud detection and risk exposure analysis

  • Safely manage customer data

  • Build AI solutions for financial advisory

  • Use virtual assistants for customer support


  • Improve service personalization and product recommendations

  • Apply predictive analytics for demand forecasting

  • Streamline visibility at all supply chain stages

  • Implement self-service assistants for customer support


  • Use predictive maintenance

  • Build solutions for remote management and autonomous control

  • Monitor manufacturing conditions and detect anomalies

  • Use neural networks for manufacturing simulations

Machine learning tech stack

  • Python

  • R

  • Numpy

  • Scipy

  • Pandas

  • Scikit learn

  • H2O.Ai

  • Keras

  • Tensorflow

  • Theano

  • Caffe

  • Google cloud

  • Amazon web services

  • Microsoft Azure

  • Apache Spark

  • Hue

  • Apache tez

  • Hadoop

  • Sqoop

  • Matplotlib

  • Django

  • Seaborn

  • Plotly

  • Flask

  • PostgreSQL

  • Jupyter

  • Elk Stack

  • Apache Airflow

  • Hive

  • SQlalchemy

Looking for different solutions or technologies? Let us know and we’ll see what we have to offer.

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Our approach to ML and AI development

Data source 1

Data source 2

Data source 3

Get data from multiple sources into a single system, e.g. a data lake

Extract, transform, and load structured data to the data warehouse

Build up specific datasets and prepare targets

Use ML for prediction modeling

Deliver predictions made in the form of reports

Need AI and ML experts?

We have experience building cost-effective machine learning (ML) solutions for handling complex issues, initiating new business models, speeding up fraud detection, using AI for mobile app development, and more.

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