Meetrics - BigData log processing
Real-time log processing, similarity clustering and classification
Java PostgreSQL Kafka
Implement a system to realtime log processing, group them by similarity and subsequent semi-manual classification
Engagement model
Time & Material
Marketing & Media
DevOps 1
Engineers 3
Project Manager 2
UI/UX designer 1
Company name
Meetrics GmbH
Business activity
Leader in measuring advertising visibility

Meetrics - BigData log processing

Meetrics is a fast growing leader in measuring visibility of displaying advertising with an idea of precise controlling online advertisement campaigns. Thanks to their detailed reports and benchmarks the advertiser can significantly improve conversion and last but not least, verify the proper audience and provide brand safety by excluding inappropriate advertisement content.

Case highlights

Real time log processing
Mobile Java built-in library for log collection on mobile devices
Clustering logs by similarity
Convenient web UX to approve machine classification
Automatic log classification by pattern defined by operator


Our client had an issue of not being able to scale to processing a large amount of logs, coming from multiple ad campaigns. Initially the classification was done by an operator and the cost of manual approval of every log event soared, not to mention the operator hiring process was a bottleneck.


First, we realized that if we group logs by similarity and do the approval in batches, the process will significantly speed up. That was our fast and dirty solution. Then on top of it, we applied machine learning classification techniques to pre-classify these batches, so the approval itself became much faster. Finally, we developed a convenient user interface for manual approvers. The result was an almost ten-fold faster workflow.


Hendrik Schumacher
Director of Technology
" I was completely satisfied by the technical abilities and performance of Offsiteteam. They implemented the system exactly according to our requirements and precisely in time. Their team was also very proactive, proposing their own solutions. "
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