
Redslim
Data harmonization services for CPG and healthcare sectors.
Date | Investors | Amount | Round |
---|---|---|---|
investor | €0.0 | round | |
* | N/A | Buyout | |
Total Funding | 000k |

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Redslim, founded in 2013 by Eric Bensimon, Alberto Alcaniz, Soren Altmann, and Patric Mezei, is a data service company specializing in transforming fragmented data into analysis-ready datasets. Headquartered in Zug, Switzerland, the company primarily serves global clients in the Consumer-Packaged Goods (CPG) and Consumer Healthcare (CHC) industries, including major brands like Mars, Danone, and L'Oréal.
The company's core business revolves around data harmonization and integration. It utilizes a proprietary technology platform to ingest, clean, and harmonize large, complex datasets from over 50 data agencies and more than 60 countries. This process turns siloed data from diverse sources, such as retail measurement, e-commerce, and consumer panels, into unified, analytics-ready assets. Redslim's services are designed to feed directly into a client's own business intelligence tools and data lakes, or they can be delivered through Redslim's proprietary visualization solution, Redslim SPRINT. This enables clients to gain a holistic view of brand performance, market share, competitive intelligence, and marketing effectiveness.
The business model is service-based, functioning as an extension of its clients' analytics and business intelligence teams. In November 2024, the European private equity firm Astorg acquired a majority stake in Redslim, with the founders reinvesting significantly. This partnership aims to accelerate research and development, scale the commercial teams, and drive international expansion beyond Europe.
Keywords: data harmonization, data integration, CPG data, consumer healthcare data, business intelligence, data management, market measurement, retail intelligence, data analytics, data transformation, FMCG, consumer data, omnichannel analytics, data-as-a-service, market intelligence, competitive intelligence, data visualization, data engineering, syndicated data, data lake solutions