Core contributor across TOREADOR (Analytics-as-a-Service), EW-Shopp (data analytics for marketing), DataCloud (big data pipeline lifecycle), and EDI (big data incubation).
JOT INTERNET MEDIA ESPANA SL
Madrid-based SME specializing in big data analytics for marketing, data pipeline engineering, and European data ecosystem development.
Their core work
JOT Internet Media is a Madrid-based digital marketing and data analytics SME that specializes in turning big data into actionable business insights, particularly for advertising optimization and e-commerce. They build data-driven tools and platforms that help businesses make smarter marketing decisions using structured and open data sources. In EU projects, they contribute applied expertise in data analytics pipelines, digital advertising technology, and business development support for data-driven startups and SMEs.
What they specialise in
Founded on ad-tech optimization (YODA — their only coordinated project) and continued with EW-Shopp connecting weather/event data to shopper marketing.
DataCloud (2021-2023) focused on data pipelines, workflows, edge computing, and blockchain — a significant technical step-up from earlier analytics work.
Participated in EDI (European Data Incubator) and REACH (data value chains incubator), supporting SME business development and cascade funding programs.
How they've shifted over time
JOT IM started in 2015-2016 with a narrow focus on digital advertising optimization (YODA) and Big Data Analytics-as-a-Service (TOREADOR), essentially applying data analytics to marketing problems. From 2018 onward, they broadened significantly into data ecosystem building — participating in incubator programs (EDI, REACH) focused on open data, data markets, and European data spaces, while also deepening their technical capabilities in data pipeline engineering and edge computing (DataCloud). The trajectory shows a company that grew from a marketing-tech specialist into a broader data infrastructure and ecosystem player.
Moving toward data infrastructure and European data space initiatives, positioning themselves as a practical SME voice in the data economy rather than a pure ad-tech player.
How they like to work
JOT IM operates primarily as a participant (5 of 6 projects), with only one coordination — their earliest and smallest project (YODA, EUR 50K SME Instrument). They work across a wide network of 65 unique partners in 16 countries, suggesting they are comfortable integrating into diverse consortia rather than building tight repeat partnerships. Their typical contribution appears to be applied data analytics and business-side expertise rather than fundamental research leadership.
Broadly networked across 16 countries with 65 unique consortium partners, indicating diverse European connections rather than a concentrated regional cluster. Their partnerships span research institutions, tech companies, and incubator ecosystems.
What sets them apart
JOT IM bridges the gap between big data technology and real business application — they are not a research lab building algorithms, but a company that knows how to turn data analytics into marketing results and business value. Their dual experience in both technical data projects (TOREADOR, DataCloud) and ecosystem/incubation projects (EDI, REACH) makes them an effective partner for consortia that need someone who can connect technical outputs to market adoption. As a Spanish SME with genuine product experience (digital advertising), they bring commercial credibility that pure research partners often lack.
Highlights from their portfolio
- DataCloudSecond-largest funding (EUR 355,000) and most technically ambitious project, covering data pipelines across the computing continuum including edge computing and blockchain.
- YODATheir only coordinated project — an SME Instrument Phase 1 for automated digital advertising optimization, revealing the company's commercial origin story.
- TOREADORLargest funding (EUR 363,750) — built a trustworthy model-aware analytics platform, representing their deepest technical engagement in big data.