Machine Learning Services

We provide organizations with an innovative machine learning solution that can help them overcome many of their business challenges.

Systematic’s Machine Learning Services

We provide organizations with an innovative machine learning solution that can help them overcome many of their business challenges. By leveraging ML-powered applications, we help you make data-driven decisions.

We have developed the capabilities to provide strategy, design, engineering solutions, and research & development services to Fortune 100 companies and enterprises by delivering best-of-breed machine learning + artificial intelligence software solutions for IoT applications, data services, and digital transformation. We focus heavily on R&D as a service, helping companies to bring their idea to life by creating a working proof of concept and making it mature enough for the full scale.

Our Machine Learning Services

Data Science

Take advantage of meaningful insights to make your product or service better.

Natural Language Processing

Build natural interactions with your users and identify patterns in unstructured data.

Data Engineering

A data scientist will get your data ready so that your AI algorithms will be able to maximize its potential.

Computer Vision

By combining machine learning techniques with deep learning techniques, we are able to gather relevant and actionable information from video and image files.

Predictive Analytics

As part of our approach to identifying underlying patterns, we design, build, train, and deploy an ml model and deep learning models.

Deep Learning

By applying deep learning techniques, forecasting, decision-making, and other key operations can be performed more efficiently.

Recommender Systems

Utilize a recommendation system that provides accurate results to create an individualized experience for every user.

Our Methods in Machine Learning
and Data Science Projects

We begin each project by analyzing your business needs, documenting your requirements, and developing your vision for a solution that will connect information and value.

After reviewing your current data infrastructure, we look at your datasets and find out if there are anomalies, missing values, dependencies, and patterns that need to be rectified.

As part of the preparation phase, we clean and transform the data into a unified format before we begin modeling it.

To determine which model provides the most accurate outcome, our data scientists train many models. Based on the accuracy of results, simplicity, and performance of each model, we then choose the best model.

It doesn’t matter if you’re building an enterprise business intelligence (BI) product, a machine learning algorithm, or a data management solution, we engineer, interface, and validate your product as we help you adjust to your new cutting-edge abilities.

In order to maintain growth and establish long-term client/vendor relationships, we offer our clients and partners dedicated staff to guide them as they release new innovations, add more tools and data sources, and integrate their products further into their workflows. Our goal is to establish long-term client/vendor relationships where we support each other’s development.

Machine Learning at the Edge

Edge computing shifts processing power closer to the point of data generation in order to reduce network congestion and inactivity periods, thereby securing the maximum benefit from your data. Through this method, companies can use this information to improve the results of their business operations. It is important to note, however, that edge computing does not provide a quick fix for all business outcomes.

Businesses must account for the constant growth of data.

Applications at the edge continue to generate massive amounts of information, and often, organizations need to make decisions in real time based on that data. A key approach to doing this is through the implementation of artificial intelligence (AI) and machine learning (ML). AI and ML are allowing companies to make sense of their data and extract the maximum value out of their assets, while also speeding up the push to the edge.

A machine learning service can help achieve your business goals and fuel your digital transformation through improvements in customer experiences, employee productivity, cost reduction, and fraud reduction. The problem is that determining where to start when applying machine learning can be challenging. You can eliminate this barrier for your organization by implementing practical and proven machine learning tools that can quickly translate into real business benefits.

Smart Retail and Call Centers

Machine learning can improve customer service by providing personalized customer interactions, voice sentiment analysis, and live call analytics.

Data Extraction

Extract text and data instantly from virtually any document to uncover valuable insights, enact human reviews, and process millions of pages in hours without manual effort.


Automate the tracking of potentially fraudulent online activity, including payment fraud and fake accounts through machine learning.

Curated Customer Recommendations

Use machine learning algorithms to enhance your user experience through individualized online experiences by tracking user preferences and browsing patterns for targeted marketing or personalized entertainment recommendations.

Machine Learning Platforms We Use

  • AWS Machine Learning: Amazon SageMaker
  • Google Cloud Machine Learning Engine
  • Microsoft Azure: Azure Machine Learning Studio to develop a machine learning model
  • Open Source Machine Learning Frameworks: TensorFlow, Theano, and Keras

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