At Mystic, we specialize in solving complex problems and work toward simple solutions for our clients unique problem space and the right technology for the task. We've written books on the subject of machine learning so let us shed light on how these cutting-edge technologies can revolutionize your business operations. From harnessing the power of AI to streamline processes, to achieving insights with our data scientists and machine learning models, we provide real-world examples of our tailored solutions in action. Get ahead of your competition as technology intersects with innovation, unlocking endless possibilities.
The Power of AI, Machine Learning & Data Modeling
The Road to Singularity
The Problem
Twitter had long been running advertising campaigns for customers and due to the hodgepodge and non-deterministic nature of the backend infrastructure they could not reliably identify problems nor enhancements to running campaigns. A decade of infrastructure changes from Ruby on Rails to JVM and Python and non-standard nor controlled methods of logging the nature of how a campaign went from start to running to finish had become a revenue and data black box.
.png)
The Solution
Through building out Goldtracer, our campaign debugging tool, we were able to provide real-world feedback to customers running thousands to millions of dollar campaigns. We utilized a combination of data collection with ETL processes dumping petabytes of data into a data lake and carefully crafted machine learning models to massively refine the data necessary to provide insights to customers. With this in place we could feed recommendations to current and historically running campaigns, to internal customer management teams, and to the ad management platform.
The Result
With these enhancements, Twitter was able to streamline their ad campaign operations and remove troublesome code paths. They have been able to offer near real-time guidance - based on the data collection and machine learning models - on how to better target their campaigns to create a more positive outcome, up to 10% better than earlier campaigns. Through our innovative approach of leveraging a large amount of data, using machine learning models to operate only on the most useful data they had been able to unlock new revenue potential and successfully sell the company to the then richest man in the world.
.png)
Empowering Twitter's Evolution into an Ad Targeting Powerhouse: Our Role in the Transformation
Aerospace Case Study
Let us know how we can be of service. We are always available for discussing business opportunities, media inquiries, or just to talk.
Looking for job opportunities? We'd love to
hear from you too.
Get in Touch
Twitter had long been running advertising campaigns for customers and due to the hodgepodge and non-deterministic nature of the backend infrastructure they could not reliably identify problems nor enhancements to running campaigns. A decade of infrastructure changes from Ruby on Rails to JVM and Python and non-standard nor controlled methods of logging the nature of how a campaign went from start to running to finish had become a revenue and data black box.
Through building out Goldtracer, our campaign debugging tool, we were able to provide real-world feedback to customers running thousands to millions of dollar campaigns. We utilized a combination of data collection with ETL processes dumping petabytes of data into a data lake and carefully crafted machine learning models to massively refine the data necessary to provide insights to customers. With this in place we could feed recommendations to current and historically running campaigns, to internal customer management teams, and to the ad management platform.
With these enhancements, Twitter was able to streamline their ad campaign operations and remove troublesome code paths. They have been able to offer near real-time guidance - based on the data collection and machine learning models - on how to better target their campaigns to create a more positive outcome, up to 10% better than earlier campaigns. Through our innovative approach of leveraging a large amount of data, using machine learning models to operate only on the most useful data they had been able to unlock new revenue potential and successfully sell the company to the then richest man in the world.
Mystic brought us the 5 Days of Wicket article series, as well as the Apache Wicket Refcard -- both contributions have been extremely popular on DZone. Our editorial staff was impressed with Mystic's domain expertise and professionalism -- we look forward to working with them again in the very near future
Nitin Bharti
VP Group Publisher
DZone
Andrew is an excellent person to work with. Insightful, direct, cuts to the important stuff without a lot of worrying about irrelevant stuff. Goal-driven, and a lot of fun to work with. Plus, he learns well - a skill that I value very highly, because that means that not only can he learn from others, but he can teach.
We asked Mystic to come in to our company to train 18 of our technology leaders for five days covering everything from the basics to very advanced use cases that we presented for our planned large scale implementation and integration... was flexible and in-depth, and we have a lot of momentum on our journey to success with Wicket.
Randal Schnedler
Lead Technical Architect
USAA
The Problem
Twitter had long been running advertising campaigns for customers and due to the hodgepodge and non-deterministic nature of the backend infrastructure they could not reliably identify problems nor enhancements to running campaigns. After over a decade of infrastructure changes from Ruby on Rails to JVM and Python and non-standard nor controlled methods of logging the nature of how a campaign went from start to running to finish had become a black box.
The Solution
To address these multifaceted challenges, we implemented a comprehensive solution leveraging the power of artificial intelligence (AI) and machine learning (ML). By harnessing passenger in-flight behavior, we developed a dynamic system tailored to individual preferences. Additionally, our team utilized aircraft in-flight data to generate detailed analytics, providing insights into all visible operational aspects and identifying areas for improvement. Furthermore, we integrated a crew management component into the platform, optimizing catering and logistics processes to enhance overall efficiency and revenue generation.
The Result
The implementation of our solution is ongoing, and our aerospace client has recognized significant growth and partner opportunities driving increased ancillary revenue and the SaaS platform optimizing fleet management and operations, our client is poised for continued success in the aerospace industry. Moreover, the planned crew management component is targeted to improve operational efficiency, paving the way for sustained revenue growth and improved customer satisfaction. Through our innovative approach leveraging AI, ML, and data analytics, our client continues to unlock new possibilities for growth and profitability.
