AI Services

Artificial Intelligence

AI services are elevating decision-making precision by creating efficiencies, saving costs and delivering new solutions to critical problems

We Provide AI Solutions To Organizations Implement This Technology

Providing artificial intelligence solutions, consulting and AI software development to start-ups and large enterprises, we noticed that although the company structures may be totally different, both start-ups and enterprise clients face the same challenges planning new data initiatives. Our clients either don’t have their own data science teams, or their team is too small to cope with all the tasks in the environment of a fast-growing company. With Sattrix Software you’ll save time on hiring top-notch specialists. Our engineers will bring know-how to your project from day one.



We build the foundation for cognitive business by working with complex technologies and rapidly evolving business environment, to offer project performance optimization.

Machine learning

Leveraging our cutting-edge Machine Learning platform, we’re taking advanced analytics and model building to new heights for our clients. Our approach is a highly dynamic framework which utilizes simultaneous training of multiple algorithms for each project. Algorithms adapt to new sets of training data, allowing them to get stronger over time as the latest campaign results are analyzed and the algorithms further refined.

Data Strategy

Start your AI Journey with an elaborate data strategy tailored to your unique business goals. Sattrix Software can help you find use cases for AI & Machine Learning. Create a data strategy, design big data architecture.

Predictive modeling

We build AI solutions to help you anticipate customer behavior and outcomes and steer your business in the right direction. Our predictive analytics services include data strategy consulting, custom machine learning model development, end-to-end predictive analytics software development.

Data Integration

Collaboration of technical and business processes to combine data from disparate sources and provide a unified view of data of the company's data assets for retrieval of meaningful & valuable information.

Data Processing

Manipulation & processing of data into usable form using a predefined sequence of operations done either manually or automatically to get meaningful insights enabling users to choose output that suits the requirement.

AI Software Development

Collaboration of technical and business processes to combine data from disparate sources and provide a unified view of data of the company's data assets for retrieval of meaningful & valuable information.

We Successfully Cooperate With Different Teams
Within Your Company

  • Data Science teams

    In cases when a company already has a data science team we become a valuable asset bringing profound expertise in certain areas of artificial intelligence, such as computer vision, natural language processing, predictive analytics.

  • Data Engineering teams

    Machine learning may not be the key expertise of your company. In this case, we are working with an existing engineering team providing the API of a machine learning system that fully corresponds to your needs and requirements. This way we allow your team to focus on their primary tasks rather than try to learn an entirely new discipline.

  • Business units

    This type of cooperation often starts with developing a proof of concept for a business unit. Typically, the stakeholders are non-technical people who have very “high level” goals. We work closely with them breaking down this goals into logical steps, defining and prioritizing use cases, and providing the best solution for each use case in order to achieve complex results.

How We Solve Problem?


Reviewing your current capabilities and defining future goals to make recommendations for tools, technology, and architecture.

Proof of Concept

Test a small-scale system, proving the viability of the machine learning models for your problem.


Improvement of previously built models to continuously raise the quality of insights and to keep up with the changing environment.


Inserting the machine learning system into production while considering costs of implementation and maintenance during deployment.