High-Impact Data Engineering


Gain actionable insights, make informed decisions
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Solid data architecture. We implement a scalable data architecture that ensures data is collected, integrated, validated, and delivered to key stakeholders.
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Scalable data platform. We create platforms to store and process large volumes of data, facilitating smooth data flow, and supporting real-time analytics.
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Robust data pipelines. Our team designs data pipelines that consolidate information from various sources, enabling analytics, visualizations, and actionable insights.
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Long-term data strategy. We work with you to develop a scalable, data-driven strategy that adapts to increasing data volumes, ensuring long-term success.
Why seek support with data engineering?
In our clients' words
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The partnership allows us to build a best in class product.
60% more engagement with hyper-personalization
Netguru developed an AI-powered solution for Newzip, a real estate-as-a-service platform, to drive hyper-personalized user experiences. The proof of concept integrated customer data to provide tailored insights, enhancing interactions between home buyers, agents, and lenders.
This resulted in a 60% increase in engagement and a 10% boost in conversions, confirming that personalized experiences can effectively drive user engagement and platform loyalty. The solution was scalable, handling more than 10,000 users nationwide.

Speeding up Merck’s process from 6 months to 6 hours
Merck wanted to reduce the manual effort of identifying chemical compounds from scientific literature. We implemented an AI-powered R&D Assistant to automate data extraction and analysis.
Within just 5 weeks, we delivered a proof of concept hosted on Merck’s secure AWS infrastructure, utilizing their own GPT service. The AI solution reduced the process from 6 months to a mere 6 hours, drastically improving efficiency and freeing experts to focus on strategic tasks.

Top challenges we solve
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Inefficiencies. For Libra, we streamlined the time-consuming process of manual data labeling by creating a platform that delegates annotation tasks to users.
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Poor data quality. For CLARIN-PL, we built a high-quality dataset of valid and abusive clauses from real documents, enabling the NLP model to accurately classify and differentiate between them.
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Scalability with big data. For NeedEnergy, we used AWS and Docker to create a scalable platform that improves energy predictions as data grows.
Why Netguru?
15+
Years on market400+
People on board2500+
Projects delivered73
Our current NPS score