Situation
Keboola, a leading provider of data operations solutions, empowers organizations to manage complex data workflows. With the rapid growth of the AI and data sectors, staying on top of new market trends and identifying emerging data companies had become a priority for Keboola. Their existing process, while functional, relied heavily on manual inputs and multiple tools, making it increasingly difficult to scale. As the industry evolved, Keboola realized that it needed a more streamlined, automated solution to enhance the efficiency of tracking and analyzing these trends.

To ensure they could continue to lead the market with innovative solutions, Keboola needed a way to integrate insights from a variety of data sources—both structured and unstructured—without overcomplicating their workflow.

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Problem
The product and research teams at Keboola were using a variety of tools, including Slack, Notion, Make.com, OpenAI, and their own platform. This multi-tool system was effective but ultimately led to challenges in governance, observability, and cost monitoring. The use of so many disparate tools made it difficult to get a unified view of market movements, and monitoring total costs across the entire setup was nearly impossible. Moreover, existing AI tools for generating structured insights from unstructured data sources often produced inconsistent or unreliable results.

While this approach worked, it was clear that as the volume and complexity of data increased, so too did the need for automation and more effective integration of insights into their workflows.

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Solution
Keboola found the solution in Roe AI, integrating its robust unstructured data capabilities with their existing platform. Roe AI’s powerful data analysis tools were able to transform unstructured data—such as web pages, documents, and social media—into structured insights, providing a more reliable and consistent view of emerging trends. This automation allowed Keboola to continue using its existing infrastructure while reducing the number of tools involved in data collection and analysis.

Roe AI enabled Keboola to query enriched, structured insights using familiar SQL interfaces, seamlessly blending with Keboola’s data workflows. By automating the data enrichment process, Roe AI allowed Keboola’s teams to focus on higher-level analysis rather than manual data tagging and processing.

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Business Impact
The integration with Roe AI led to significant improvements in both efficiency and accuracy. The time required for market research tasks was reduced by 30%, allowing teams to shift their focus from data collection to strategic analysis. Moreover, the accuracy of structured insights increased by 50%, making the research process not only faster but more reliable.

This integration also helped Keboola solve governance and observability challenges, offering a clearer view of data flows and enabling more effective cost monitoring. By consolidating data sources and reducing reliance on multiple tools, the complexity of the system was reduced without sacrificing the quality or depth of insights.

The result was a more agile, efficient, and cost-effective approach to market research, enabling Keboola to stay ahead of industry trends and capitalize on emerging opportunities.

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Conclusion
Partnering with Roe AI has empowered Keboola to automate key aspects of its market research processes, enhancing both the speed and accuracy of insights while maintaining strong governance and observability standards. The collaboration has not only streamlined operations but also provided a more reliable and scalable solution for future growth.

By leveraging Roe AI’s capabilities, Keboola has been able to simplify its data workflows, improve the reliability of AI-generated insights, and focus on delivering high-value strategic outcomes. This partnership illustrates the power of automation in modern data operations and highlights how AI can drive meaningful improvements in business processes, even in complex and fast-moving industries like AI and data management.

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