Current AI development is fundamentally broken
Up to 85% of AI projects fail to make it to production. But inevitably all organizations have to innovate and become AI and data science organizations to enable data-driven decision making, solve problems faster, and stay relevant.
Interdisciplinary collaboration is the key
The Omdena advantage is to get access to cross-functional teams with a mix of skills and perspectives. Our diverse teams of up to 50 collaborators are able to do data innovation, apply the latest tools, and make end-to-end AI development accessible.
Our results-driven and innovative development model has resulted in a global track-record of successful use cases.
Combining data from multiple sources, types, and disciplines
Having a single source of data is often not enough to solve a real-world problem. Omdena´s interdisciplinary teams are able to identify and combine structured and unstructured data most effectively.
For example, to build a model to map areas for solar adoption in Nigeria (see left image) we used satellite images to identify the population density in a particular area and combined it with Google Search data to understand the business landscape.
From hierarchical silos to networked teams
Traditional organizational structures are not designed to enable successful AI development.
Our projects are powered through bottom-up collaboration characterized by open dialogue, where diverse ideas are shared freely to find the best solution to a problem. Our test-and-learn mentality incorporates feedback early on and speeds up agile development to deliver results where they are most needed.
Unlocking the value of Collaborative AI
Fast & agile development
months only is the average duration of a project where up to 50 collaborators deliver a functional solution.
nationalities in average represented per project in combination with diverse skills and processes for knowledge sharing make new ideas flourish.
women in our projects, paired with technical and non-technical team members help to prevent bias and develop inclusive and trusted solutions.
What our partners say about us
We’re really excited about the results of this project. My team currently uses the code and infrastructure on almost a weekly basis.
John BrandtData Scientist, World Resources Institute
Omdena is making a real change in building AI solutions for meaningful problems.
Kirk BorneWorldwide #1 Top AI Influencer
Omdena is a revolutionary idea and by far the best thing I saw in 2019. The biggest value is the delivery of a working solution in a very precise timeframe (8 weeks).
Semih BoyaciCo-Founder Impact Hub Istanbul
This is an amazing project. I really love the direction Omdena is setting. A real positive and visible influence in the field.
Brandon RohrerGlobal AI influencer
A great collaborative experience for mission-driven organizations and UN agencies with limited resources and AI expertise. The biggest value we have experienced is the great diversity of backgrounds and ideas.
Rebeca Moreno JiménezUNHCR Innovation
Omdena’s community accomplished in 8 weeks what we tried for two years while working with large corporations. I can say Omdena is one of the world’s finest set of Data Scientists working for Social Good.
Rahul Ranjan SrivastavaTech Lead, Safecity
The collaborative approach of Omdena is taking innovation to a whole new level. We are proud to have worked together on addressing zero hunger in our “crop’s identification challenge”. We believe this is the start of a long journey together.
Saurav SumanUN World Food Program Nepal
Outstanding in many ways! The challenge provided Sintecsys’s Team an intense and accurate deep dive into AI with amazing results. For Sintecsys, from now on, Omdena is the official AI partner.
Osmar Rossetto Bambini FºHead of Innovation, Sintecsys
Omdena Collaborators come from various backgrounds
Data Scientist at Microsoft
Colton Magnant, Ph.D.
Professor and Lead Data Scientist at UPS
Ph.D. Student Machine Learning, AI Education Lead at Zaka
Operations Analyst at Google
Data Scientist at BASF
CS Masters Cambridge, Senior ML Engineer at Aigorithm LLC
Data Scientist at Enexis Groep
Rosana de Oliveira Gomes
Postdoc Physics, Frankfurt Institute for Advanced Studies
How it works
Once an organization has submitted a feasible project, we source a high-performing team.
The team analyzes the problem from various angles to prioritize for impact and feasibility.
Data collection and preparation
Different task groups identify innovative ways to collect and augment multiple data sources.
Through our unique collaborative processes and fast iteration cycles we build the best-fit model.
We extend the model to a production-level solution with continuous updates & maintenance.
Connect with us in our live chat below.