Artificial Intelligence (AI) is a field that is rapidly developed and increasingly adopted in industry to automate routine labor, understand text, visual or audio content and support scientific research.

Who is AI for?

All businesses, from early stage startups to enterprises, are exploring ways that AI can help them redifine workflow processes and create new consumer experiences.

AI can give any business a competitive edge:


Digital asset management as well as media and personalized content creation for advertising.

System Admin

Predictive maintenance and resource optimization to manage infrastructure performance.



Fast data analysis and experimental parameter optimization to make new scientific discoveries.

Product Manager

Sales prediction to manage inventory and gain customer insights.

Customer Support

Chatbots, voice assistant technology, and machine translation to improve customer services.

How does AI work?

AI aims to solve identification, correlation, generation and forecasting problems that are ubiquitous but also easy for us to solve intuitively.

The solution lies in allowing AI models to learn from experience and understand the world in terms of a hierarchy of concepts. This approach deviates from traditional software engineering because a human operator is no longer required to formally specify all the knowledge that computers need to derive insights.

What does an AI strategy entail?

Problem Specification
A clear specification of the problem and desired outcomes.
AI is heavily reliant on data acquisition, accuracy, and provisioning. Developing supporting tools can accelerate data labelling, quality control and ensure that data is accessible to authorized team members when needed.
Effective scaling relies on anticipating long-term aspects of your strategy, such as operation costs as your data volume increases. In many cases, the process of using a trained model to make predictions, generates the greatest cost of AI.
Data and security management procedures are adopted to safeguard companies and ensure that they abide local and global regulations. Companies should determine data ownership ahead of time, verify data gathering and processing methods are lawful, consider the physical location of the servers that process your data and set evaluation methods to monitor and explain the evolution of the model.