GEOR

About the Client
Rubicon Project, established in 2007, is a premier technology entity specializing in online media buying and selling. With a commitment to innovation, Rubicon has cemented its position as a key collaborator for publishers, brands, content creators, and app developers. Their sophisticated solutions empower leading companies to engage in efficient transactions and offer seamless consumer experiences. At the core of their operations is one of the industry’s most extensive real-time cloud and big data computing platforms, managing billions of transactions monthly, employing advanced data analysis through Hadoop and Apache Spark to inform their comprehensive reporting modules.

Objective
Rubicon’s strategic goal was to enhance a subsidiary product pivotal for revenue generation, opting for a big data solution crafted by seasoned third-party engineers to preserve their internal team’s focus on primary tasks. This approach underscores the utilization of Employer of Record (EOR) services for staff augmentation, enabling Rubicon to leverage specialized expertise without diverting their core team from essential functions.

 

Challenges
The primary challenge was to manage and optimize the vast data volume Rubicon processes, necessitating a robust technology stack and a scalable team adept in big data technologies. Ensuring seamless integration with existing systems while maintaining high-performance standards was crucial for the project’s success.

Implementation and Phases
The implementation journey was segmented into strategic phases:

1. Pilot Design
Initial phase focused on establishing a robust foundation using Java, Hadoop, and Spark, tailored to meet Rubicon’s data processing needs.

2. 1st Scale-Up
Following the pilot’s success, the team expanded, intensifying the development efforts and refining the solution to enhance data processing capabilities.

3. 2nd Scale-Up
Further expansion and optimization were executed, ensuring the solution’s scalability and its alignment with Rubicon’s growing data demands.

Outcomes
By partnering with GEOR by Geomotiv for managed IT services, Rubicon achieved a threefold acceleration in staff augmentation and a significant cost reduction of 45%. This strategic collaboration enabled Rubicon to augment their market share and solidify market presence, demonstrating the tangible benefits of leveraging specialized IT expertise through an EOR model.

Client Profile
MediaMath, a pioneering AdTech entity, excels in providing comprehensive digital marketing solutions to over 3,500 advertisers and brands globally. Their robust portfolio spans programmatic media buying, data management, audience segmentation, and targeting tools. The Custom Solutions division in the UK, our collaborative partner, has acknowledged the success of numerous projects executed by our team.
 

Technological Backbone
The project utilized an extensive array of technologies: Python, Node.js, React.js, JavaScript, PostgreSQL, MySQL, AWS, Google Cloud, AMQP, MongoDB, LaunchDarkly, and the ELK Stack. This diverse tech stack underscores our commitment to leveraging cutting-edge tools to deliver bespoke solutions.

Objective
The engagement aimed to provide MediaMath with a full-time, proficient team in AdTech to enhance existing features, develop new components, and ensure seamless platform integration. Adhering to the Agile methodology ensured continuous iteration and improvement throughout the project lifecycle.

Project Synopsis
Our journey with MediaMath began over five years ago, embarking on a mission to create an automated technical solution for advertising campaigns. The need was for a team adept in AdTech to augment the platform’s functionalities and introduce innovative features, a role Geomotiv was poised to fill.

Project Highlights
Our team has developed dozens of sub-solutions of varying types and complexity over more than 5 years of working with MediaMath.

White-label Ad Management System
Tailored for clients desiring a simplified version of MediaMath’s DSP, this system retained core functionalities while eschewing unnecessary complexity, offering unparalleled flexibility and user-centric adaptability.

Scheduler System for Ad Campaigns
Embedded within the client’s DSP, this system provided a user-friendly interface for managing advertising schedules, employing intricate logic and a comprehensive feature set for schedule manipulation.

Graphical Ad Campaign Analysis
This standalone module allowed for the visual representation of campaign data, aiding in the intuitive analysis of advertising outcomes.

AdTech Entity Validator
A Python-based tool enabling MediaMath to authenticate campaign-related data, this validator is accessible as a reusable component, enhancing efficiency across teams.

Automated Testing Package
Developed to enhance testing efficiency, this package, stored in a private repository, offers a standardized approach to software validation across teams.

Feedback Collection Website
This platform streamlines user feedback for MediaMath’s AdTech solutions, directly channeling insights to the support team for analysis and action.

Development Boilerplate
To expedite future developments, a standardized project template was created, housing ready-to-use modules and accelerating the development process.
Execution Phases
Business requirement analysis and architectural design set the foundation for the project.
Agile development cycles facilitated iterative progress, encompassing development, testing, and deployment phases, culminating in the release.
Outcomes
Our partnership with MediaMath exemplifies the power of collaborative innovation in AdTech. The suite of solutions delivered has not only enhanced the operational prowess of MediaMath’s platforms but also significantly enriched the advertiser experience, fostering loyalty and operational efficiency. The strategic development initiatives have poised MediaMath for sustained success, minimizing future maintenance costs and streamlining development workflows.

Client Background
MedWhat stands at the forefront of medical technology innovation, with its foundations deeply rooted in the expertise of a diverse team comprising doctors, data scientists, artificial intelligence PhDs, and medical researchers from Stanford University. Based in the technological heartland of Silicon Valley, MedWhat has dedicated over seven years to pioneering medical research with the aim of enhancing patient care, minimizing diagnostic uncertainties, reducing human errors, and elevating the quality of medical services. Their visionary endeavor led to the conceptualization of a medical chatbot designed to support healthcare professionals by offering medical consultations, enhancing patient outcomes, and optimizing operational efficiencies.

 

Tech Stack
The project leveraged a sophisticated array of technologies including HTML, CSS, JavaScript, MySQL, Bootstrap, Java, Gradle, and Azure to create a robust and responsive solution.

Objective
MedWhat sought to develop a patient-centric digital assistant that could revolutionize the way healthcare providers interact with and manage patient care. The envisioned chatbot was designed to offer precise medical information tailored to individual health records, aiming to support healthcare entities such as insurance companies, hospitals, and pharmaceutical firms, ensuring alignment with their operational requirements.

Project Execution
Leveraging their proficiency in crafting similar digital solutions, GEOR by Geomotiv employed a strategic approach to this project. The development team, proficient in artificial intelligence and machine learning, crafted a dynamic application capable of adapting to patient-specific inquiries. The chatbot’s intelligence was underpinned by a continuously updated knowledge base, incorporating real-time patient health records and historical medical queries to deliver informed and accurate responses.

Project phases
Procurement of Business Requirements 
Initial phase involved in-depth consultations with MedWhat to understand the precise needs and compliance requirements of the targeted healthcare sectors.
Architecture Design 
The team formulated a robust architecture plan, ensuring the chatbot’s scalability, security, and integration capabilities with existing healthcare systems.
Back and Front End Development 
Focused on creating a user-friendly interface while establishing a strong, reliable backend infrastructure to process and respond to user queries effectively.
Code Refactoring 
Continuous refinement of the code ensured optimal performance, maintainability, and scalability of the application.
Quality Assurance
Rigorous testing phases were implemented to ensure the application’s reliability, accuracy, and user-centric functionality.
Production Deployment 
Following successful testing and refinement, the chatbot was deployed, ready to transform the patient-care landscape.
Outcomes
Through this collaborative venture, GEOR by Geomotiv and MedWhat achieved the timely development of a groundbreaking AI-driven medical chatbot. This achievement played a pivotal role in supporting MedWhat’s ongoing fundraising initiatives, positioning them as innovators in the medical technology space. The project not only underscored GEOR by Geomotiv’s expertise as a professional IT services procurement company but also demonstrated their ability to deliver cutting-edge technological solutions that align with the strategic objectives of their clients in the healthcare industry.

BBG was looking for a technology ally that could align with their business goals and augment their staff to manage ongoing projects. The ideal partnership would include a cadre of experienced web engineers.

We advance medical consultation with AI by providing a professional mobile application development team. that was MedWhat's collaboration with GEOR by Geomotiv. The customer managed to maintain high quality of madical service and avoid costly and time-comsuming IT developers recruitment.

GEOR by Geomotiv successfully integrated an external ad network for Rubicon Projects. It allowed the client to automate its advertising. In addition to successfully completing the project, we managed to recruit a team of professional IT programmers and designers with marketing expertise.

Savveo partnered with GEOR by Geomotiv for Unified AdTech Platform Development. We provided fast and professional IT staffing services that allowed the client to avoit time-comsuming and costly in-house hiring. Also we provide workforce management software to streamline time and cost tracking.