Machine Learning Solutions

Intelligent Systems

We build machine learning systems that gather and analyze data as well as communicate with other systems to better inform our clients to make strategic decision based on their data.


Our intelligent systems include the capacity to learn from experience and the ability to adapt to current data through automatic algorithm optimization.

Intelligent systems enable our clients to run simulations, identify unknown relationship among their data, and predict future outcomes.


We accomplish this by leveraging custom built supercomputers, our deep technical and data science expertise, and tapping into various machine learning techniques such as:

  • Supervised, Unsupervised, and Reinforcement Learning

  • Deep Learning Neural Networks

  • Graph Neural Networks

  • Recommendation Engines

  • Hadoop and Spark

  • Serverless computing

  • Continuous Integration and Continuous Deployment

 

Cloud Architecture Solutions

Microservices and Serverless

We work with our clients to build applications leveraging microservices and serverless architecture. This allows software to be broken down into multiple component services, so that each of these services can be continuously deployed independently without compromising the integrity of an application.


Microservice architecture gives developers the freedom to independently develop and deploy services. We also help develop the serverless architecture by breaking apart server-side applications into functions (FaaS) that each perform a distinct task. Some of the benefits companies experience when harnessing microservices and serverless architecture are:

  • Enhanced Scalability

  • Lower Cloud Cost

  • Reduces Human Resources

  • Decreases Time to Market

  • Increases New Features and User Experience

  • Continuous Integration and Continuous Deployment

 

Machine Learning Infrastructure

Build, Train, Deploy Rapidly

We remove hidden technical debt by building the infrastructure organizations must have in order to leverage enterprise production level machine learning. We do this by leveraging the most cutting-edge technology available in the market in order for you to build, train, and deploy machine learning models into production efficiently while remaining cost-conscious.


Building machine learning infrastructure includes:

  • Distributed Server Infrastructure

  • Data Collection and Management

  • Data Verification

  • Feature Extraction

  • Machine Resource Allocation

  • Machine Learning Code

  • Analysis Tools

  • Process Management Tools

  • Monitoring

 

Predictive Analytics

Predictive, Behavioral & Workforce Analytics

By leveraging Artificial Intelligence such as Machine Learning, Deep Learning, and Natural Language Processing we are able to build predictive models that enable our clients to predict trends, understand customers, and drive strategic decision making.

​Predictive analytics allow our clients to become proactive, forward looking, anticipate outcomes and behaviors based on their data. Predictive analytics are used to determine customer responses or purchases, as well as promote cross-sell opportunities. Predictive models help businesses attract, retain and grow their most profitable customers.


​Workforce analytics can help our clients develop and improve recruiting methods, specific hiring decisions, and keep the best employees within their company. We help our clients build higher performing teams by developing predictive workforce models that identify top performers' key characteristics and attributes. Workforce Analytics utilizes an advanced set of data analysis tools and metrics for comprehensive workforce performance measurement and improvement. It analyzes recruitment, staffing, training and development, personnel, and compensation and benefits, as well as standard ratios that consist of time to fill, cost per hire, accession rate, retention rate, add rate, replacement rate, time to start and offer acceptance rate.

Behavioral Analytics enables our clients to understand why and how their customers behave in a particular way. By incorporating behavioral analytics, we are able to provide unknown insights about customer behaviors, what influences their behaviors, and gain an understanding about their interactions.