Geomotiv

About the Client

Our client was an advertising company with an online marketplace designed to provide advertisers with easier options to compare, purchase, and track linear TV ad campaigns. 

Goal

Our main goal was to build a custom TV media selling product that automated the sales processes on television ad companies’ side and allowed them to grow sales team smoothly without incurring significant management overhead. That solution was meant to be used by third-party media buyers and TV station groups.

Work Description

As a first step, we accumulated and analysed the customer’s business requirements. With that, we defined a suitable technology stack, which comprised AWS, Java, and JavaScript as core technologies. We proceeded with inventory service integration; we used Videa and WideOrbit. After that, we developed a custom DMP to hold and process first and third party inventory sales data over the last few years. Using historical data allowed us to design and implement highly accurate custom algorithms for automated media plan generation and programmatic execution of campaigns. 

It was an engagement for full-cycle product development, thus prototyping, design, development, quality assurance, deployment, and DevOps services were part of it. 

Results

Geomotiv automated the dealmaking process conducted by the client’s agency cutting down the time spent on each deal. As a result, a major part of media planners’ work was performed automatically, which boosted the overall team performance by 50% and allowed them to focus on other areas.

About the Client

Based on its accumulated experience, Geomotiv founded its product subsidiary Adoppler (www.adoppler.com) in 2017 in order to provide faster time-to-market for the companies in the TV sector through the use of programmatic technologies. Adoppler was tasked with developing a full-stack programmatic AdTech platform (Trusted Marketplace) that would facilitate the media buying and selling process.

Goal

Develop a programmatic platform that would help clients to avoid legacy approaches and take into account both sides of the media buying process in a secure and transparent environment for AdTech transactions based on the Trusted Marketplace technology.

Work Description

As a first step, the platform became an RTB exchange that could interact with programmatic buyers and sellers based on the OpenRTB protocol. Later on, SSP capabilities were added. To achieve the possibility to conduct direct deals through a programmatic pipe, the Adoppler team built support for PMP and PG deals. Then, DSP capabilities were added. At this stage, the Trusted Marketplace made it possible to manage advertisers, their campaigns, and creatives. And finally, Adoppler developed an advanced reporting tool that added a full-stack AdTech functionality to the system. 

Results

A horizontally scalable system was developed and then tested in production with peak loads up to 20K QPS. The work was accomplished on time in compliance with all requirements declared and industry standards involved. As a result, the first version of the product was successfully introduced into international markets.

About the Client

Trusted Insight is a large California-based company founded in 2009. It provides one of the fastest-growing networks, content hubs, and software platforms used by institutional investors. Their editorial management software for journals, media organizations, publishers, content makers, and other market players has disrupted the industry. They worked with more than 200 partners worldwide and had 20,000 active users monthly.

Goal

The idea was to create a pipeline that could pull articles from the Internet and yield the extracted knowledge. The pipeline was conceived to consist of steps, or components. The extracted knowledge was to be saved into a database and then arranged for possible use. Each component consumed and produced data items of certain type.

Work Description

We divided the projected system into three main modules and dealt with each one separately:

1. Retrieval
   Perform periodic and/or real-time data retrieval from external data sources through available APIs and HTML content scraping techniques.
2. Processing
   Analyse, categorise, and store the retrieved data in a manner most efficient for end user presentation.
3. API Presentation
   A set of RESTful services that allow the front-end to consume available data on a per-user basis.

Results

The technical solution we delivered allowed the client to significantly reduce the amount of manual labor done by their content team and optimize their efficiency by 300%. As a result, the client was able to reduce operational expenses and redirect resources to other projects.

About the Client

Travelling Spoon is a California-based startup that provides travelers worldwide with authentic food experiences granted by local hosts. The customer operates in a number of countries across Asia, Europe, Africa, and South America. It is a large and experienced market player with extensive press coverage. The client’s policy presupposed close cooperation with the hosts, and the ambassador system they developed allowed them to provide a high level of quality and safety.

Goal

The customer wanted to build an app that would connect travelers and hosts worldwide and provide a quick match based on filters and travelers’ requirements. Booking and payment systems were supposed to be refined to support large numbers of real-time users. The client wanted to have a new app UI design, Facebook login authentication option, and robust dashboard.

Work Description

The app was unlike any other, so accurate business requirements were of prime importance. Such a project required a specific technology stack. As a result, the app was built based on JavaScript, Ruby, PostgreSQL, and other technologies. Our team worked in close contact with the client through all the development stages from business requirements analysis to QA and production deployment.

Results

Within two years of our cooperation, we provided full project support. We extended initial functionality and added user feedback driven features, such as new payment systems integration and referral bonuses. Our solution increased the number of monthly active users three times and helped the client to launch in new countries.

About the Client

The client is BBG, a Chicago-based award-winning interactive agency with over a decade of experience in design, development, strategy, and hosting. 

Goal

The client needed a tech partner that would understand their business needs and provide additional manpower to handle ongoing projects. Ideally, it would be a team of professional web engineers with previous WordPress, WooCommerce, and Shopify plugin integration and development experience and excellent communication skills.

With our backup, the client wanted to help brands grow and excel on the market, address their technical needs, and reduce time-to-market for their digital products. Together, we aimed at creating a partnership that could help brands stand out on the market and put them above the pack.

Work Description

The project had started prior to engaging with Geomotiv, and the team had to smoothly join in. The envisioned software had pre-defined functionality that our team was tasked with implementing keeping in mind the agreed-on schedule. Our team immediately jumped into the process and followed the scope of work as required by the project: 

• WordPress CMS development

• Technology integration

• API integration

• PHP

• Technology audit and estimation

• Backend development

Results

A fully-integrated website with easy navigation and a user-friendly interface. We continue to implement all the required functions by integrating disparate operations into a single centralized system. Geomotiv’s expertise has been vital for driving web and mobile traffic for the client since the website went live. The client also reported a solid boost in conversion rates.

We expect our partnership to continue and grow in the future as we’ve managed to go beyond the client’s expectations. Our team implements the project deliverables ahead of schedule and completes the required milestones on time and budget.

About the Client

Our client was a pioneer in a niche business segment related to digital-to-direct mail. They created a unique marketing platform with over 100 brand partners and a listing in ARF’s First Innovators A-List.

Goal

The client needed to rebuild their existing platform entirely as the business grew rapidly and the company needed a more scalable solution. The current platform was developed as a proof of concept and wasn’t designed for huge loads. In addition, the client wanted to utilize Big Data technologies to the project to ensure high performance and scalability.

Work Description

The client’s original solution was based on Python which didn’t provide enough scalability for the rising demand. The client wanted to rebuild the platform completely and implement new web features. At first, Geomotiv ran deep technological analysis and provided a new architecture plan. Our team decided on Big Data technologies such as Scala, Spark, and GraphX for the solution. The client didn’t stop the original project, so we were supporting it and creating another one at the same time. Later on we performed full data migration from the primary solution to the new one and then the client stopped the original project. Our web technologies stack comprised Java and Spring for back-end and React for front-end.

Our client had an agile (scrum) development approach and we were essentially an extension of the core team. The management process included three-week sprints, scrum meetings, backlog refinement, sprint planning, etc.

Results

Having partnered with Geomotiv, the client was able to rebuild their entire system to the new business requirements. A specialized Big Data stack helped ensure scalability and fault tolerance of the delivered solution, which original Python-based platform couldn’t provide. With that system, the client managed to reduce the costs of additional support and provide their users with a greater scope of services.

About the Client

Rubicon Project is a large technology company with a focus on online media buying and selling. It was founded in 2007 and has become an invaluable partner to publishers, brands, content creators, and app developers ever since. Their robust solutions enable the world’s leading companies to transact efficiently and deliver seamless consumer experiences.

The company operated one of the largest real-time clouds and big data computing platforms, and also collected, processed, and reported on, billions of transactions every month. They created an internal service that analyzed a large amount of data through Hadoop and Apache Spark and fed the aggregated result to the reporting module.

Goal

The client’s core requirement was to upgrade the company product that was subsidiary in terms of revenue. The client didn’t want to waste the internal team’s time and reassign that task to them for specific reasons. The client preferred to develop a big data solution with the help of experienced 3rd party engineers.

Work Description

The client was a huge company and operated with large amounts of data, so at first the team defined a technology stack. We chose Java, Hadoop, and Spark as the tools most suitable for the client’s needs. We started with a small team that grew larger in the course of time. Nonetheless, the team retained close contact with the client and ensured high quality of the end product.

Results

Having partnered Geomotiv as a staff augmentation services vendor, the client was able to accelerate their staff recruitment three times and reduce their costs by 45%. It allowed them to increase their market share and ensure continued market access.

About the Client

Natify is a digital marketing company with DSP as their core product. It acts as an advertising ecosystem within their business model. The platform enables advertisers to purchase display ad inventory via RTB exchanges, obtain account- and cookie-based advertising targeting, and make key data sets integrations. Natify’s DSP enables brands to target users on Facebook, Google Adwords, and Native Display.

Goal

The main goal was to build a system that allowed digital advertising inventory buyers to manage multiple ad and data exchange accounts through a common interface. The client wanted Geomotiv to make a microservice-oriented app out of a large monolithic platform and also to increase performance, improve flexibility and scalability, implement a range of new features, and make the whole system easy to maintain.

Work Description

The core requirements were to refactor the ad server, adjust the DSP related tool set, implement a Control Panel with new interface and functionality, and integrate Facebook that added a feature to share ads programmatically between the Control Panel and Facebook Ad Account audiences.

Results

Geomotiv created a DSP designed to be used for programmatic B2B advertising. Partnering with Geomotiv, our client was able to significantly increase their customer base and cater to their needs better.

About the Client

MedWhat is a medical technology company with a team of doctors, data scientists, A.I. PhDs, and medical researchers from Stanford University. Based in Silicon Valley, they have been doing medical research for more than 7 years to improve patients’ health, prevent indeterminate diagnosis and medication, decrease human error, and improve medical services. They came up with an idea to develop a medical chatbot that could assist doctors and nurses and provide medical consultations, improve outcomes, and reduce operational costs and personnel expenditures. 

Goal

The client wanted to build a patient-centered solution to assist healthcare providers and reduce the human factor. It was supposed to be a chatbot able to provide the patient with relevant information based on their health records. The client planned to cooperate with three types of organisations such as health insurance offices, hospitals, and pharmaceutical companies, so the solution had to comply with their businesses as well.

Work Description

The team had experience in building similar solutions, so they had a ready strategy. The engineers decided to build the app on the basis of Artificial Intelligence and Machine Learning due to the specific requests by patients. The answers were provided based on the daily updated knowledge base, patients’ health records, and medical questions history.

Results

Together with the client, we managed to develop the entire project on time to help them continue the fundraising campaign for their startup.