AI and Machine Learning

QuadraByte offers a unique perspective on AI and machine learning as the leaders in the Intelligence Economy.  Our team develops AI-driven services that enable your company to take full advantage of your organization’s data through automation, machine learning, deep learning, natural language processing (NLP), and neural networks. 

AI Solution Development

QuadraByte data scientists leverage leading-edge programming languages for the development of AI-driven solutions.

Python has been a popular programming language for many years, including facilitating data quality and cleansing, and has rapidly evolved to be a major player in the AI space.  

Developed specifically for data science, R is a newer language that has received major adoption for statistical and data analysis.

In addition, languages such as Java, Prolog, C++, and Lisp are starting to evolve their offerings to target this emerging technological space.  With the numerous advancements in this field, businesses now have many options to select a technology that fits in their current tech-stack.

Specialized Programming

Python Logo
R Programming Logo

Snowflake for AI

Snowflake’s latest feature solution, Snowpark, let’s developers leverage serverless deployment and virtual warehouses to expand Snowflake beyond SQL.  The Snowpark library provides an intuitive API for querying and processing data in a data pipeline.  This allows you to build applications that process data in Snowflake without moving data to the system where your application code runs.  

Snowpark for Python
Leveraging tools such as Anaconda, Miniconda, or virtualenv, our team can leverage the power of Python to perform many of the same tasks that you would use in a Python notebook, including packages such as numpy, pandas, and more.
Snowpark for Java
The Snowpark library provides support for distributing JAR files through Maven. You can integrate Snowpark as a dependency in your own Maven project or download the JAR file for use in your applications.
Snowpark for Scala
Snowpark for Scala lets you integrate Snowpark into your own Maven project, or SBT build files, letting you take full advantage of application development tools, REPL interactive shells, and Jupyter notebooks.
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AI/ML For Business

Augment Human Capital

Organizations can leverage AI and machine learning to automate repetitive tasks, data mapping, and other tasks to help augment human labor and increase confidence in the work performed.

Increase Profits

Investment in an AI strategy can give you strategic decision-making recommendations, such as lead or opportunity scoring, to an increase in profits.  For existing customers, your team can leverage AI to identify at-risk accounts and reduce churn.

Real-Time Decisions

Artificial intelligence helps your team drive real-time decision-making by evaluating data and providing recommendations to team members on that data, or taking direct action on that data, to ensure you always make the right move. 

Conversational AI By Vonage

QuadraByte is a preferred partner of Vonage and the Vonage AI Studio for Conversational AI.

Frequently Asked Questions

Artificial Intelligence (AI) vs Machine Learning (ML)

While AI is the broad science of replicating human capabilities, machine learning is a specific subset of AI that allows you to train a machine on how to learn.  As a whole, AI includes the subfield of ML to automate analytical model building.


Machine Learning uses neural networks, statistics, operations research and physics to surface valuable insights to your organization without first requiring explicit programming.

How does AI work?

Traditionally, computers have needed a programmer to teach them how to respond to specific actions with the use of algorithms or historical data.  AI allows data scientists to create propensity models to start making predictions and removes the need for continual development by engineers.

What data can AI leverage?

AI is capable of leveraging structured, semi-structured, and unstructured data.  Artificial intelligence lets you automate data ingestion, data mapping, exploration, visualization, or process complex data within milliseconds.