Case study

“One of our jobs is to ingest, read, analyze, and categorize millions of jobs every day”, says Paolo Santori, Jobtome’s CTO.

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In fact, when searching for employment, it’s critical that people have the tools to find a new job that matches their needs and skills quickly. To offer workers this kind of experience, we needed to provide matches that really worked, identifying the keywords job seekers use and doing the same for the signal from hundreds of other data points.

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In order to understand and interpret all those signals to refine results, the technical team needed to consolidate their technical architecture into one managed platform to better access metrics and data analytics.

For starters, we realized Google Cloud had all the solutions we needed. Using Dataflow, we managed to scale the platform’s capabilities as well as stream and process data.

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In addition, by adopting Vertex AI and machine learning, we were also able to apply its algorithms to a rich data set without the complexity of managing AI by ourselves. This way, more projects went live, more tests and experiments were run, and more value was extracted from the data we collected daily.

As a result, we had a stack that could gather, process and serve terabytes of information about jobs and scale machine learning to produce live, highly relevant recommendations. This way, the conversion rate went up by 5-10%.

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With Google Cloud, we managed to deal with far greater volumes of data and ingest, thanks to Vertex AI, 10 times the number of jobs per second, and produce a 10 times bigger number of recommendations per hour.

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These technologies, in a nutshell, helped us optimize our platform at best and reduce time on deployment and integration.

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Furthermore, Google Cloud has transformed how we do business, helping us move from a data-driven company to one powered by the insight of AI.