We are a team of Freelancers with a unique engineering and product expertise.
Our Expertise
Data Processing & Exploration
About Us
Martin Lehner
Data & Engineering
Martin has led data focused engineering teams at enterprises and startups in Berlin and London. Passionate about data architectures, stream processing and analytics he ramped up infrastructures for data processing on platforms like Google Cloud and Amazon Web Services. When not at work, he spends his free time with his daughter or on his road bike.
Christian has worked as a head of technology, product manager and software engineer with startups, mid sized companies, corporates and the United Nations. He passionately creates innovative products and loves to celebrate achievements and awards with the teams that he works with. In his free time, he climbs and surfs while travelling the world.
Analytics and reports are well-paid premium features in many SaaS business models. For a project management company we created Workstreams, a Slack based task-management solution, implementing such features through a data pipeline on AWS.
Optimizing Notifications
Delivering relevant notifications as a mobile app is crucial, especially when your product is a community-centric donation app. Setting up the complete backend infrastructure on AWS and leading the development team, we helped ShareTheMeal to great success.
Making Meters Smart
For a big British energy company, we ramped up a data infrastructure to process data streams from smart meters on Google Cloud Platform. The resulting data pipeline supplied internal business analysts, end-customer analytics and predictive algorithms.
Feeding Machine Learning
Working with a leading document-exchange company, we connected a complex platform with an external document-classifier. We significantly improved the existing solution, establishing a feedback-cycle that continuously trains the classifier's recognition capabilities.
Providing Analytics Features
Analytics and reports are well-paid premium features in many SaaS business models. For a project management company we created Workstreams, a Slack based task-management solution, implementing such features through a data pipeline on AWS.
Optimizing Notifications
Delivering relevant notifications as a mobile app is crucial, especially when your product is a community-centric donation app. Setting up the complete backend infrastructure on AWS and leading the development team, we helped ShareTheMeal to great success.
Making Meters Smart
For a big British energy company, we ramped up a data infrastructure to process data streams from smart meters on Google Cloud Platform. The resulting data pipeline supplied internal business analysts, end-customer analytics and predictive algorithms.
Feeding Machine Learning
Working with a leading document-exchange company, we connected a complex platform with an external document-classifier. We significantly improved the existing solution, establishing a feedback-cycle that continuously trains the classifier's recognition capabilities.
Providing Analytics Features
Analytics and reports are well-paid premium features in many SaaS business models. For a project management company we created Workstreams, a Slack based task-management solution, implementing such features through a data pipeline on AWS.
Optimizing Notifications
Delivering relevant notifications as a mobile app is crucial, especially when your product is a community-centric donation app. Setting up the complete backend infrastructure on AWS and leading the development team, we helped ShareTheMeal to great success.
Making Meters Smart
For a big British energy company, we ramped up a data infrastructure to process data streams from smart meters on Google Cloud Platform. The resulting data pipeline supplied internal business analysts, end-customer analytics and predictive algorithms.
Feeding Machine Learning
Working with a leading document-exchange company, we connected a complex platform with an external document-classifier. We significantly improved the existing solution, establishing a feedback-cycle that continuously trains the classifier's recognition capabilities.