Challenge
A large institution needed to enrich a database of 1.2 million companies to identify those involved in specific clean and renewable energy technologies. Additionally, they required detailed data on each company's industry, activity type (e.g., manufacturer, distributor, logistics, design and engineering, maintenance), and investment activity. The goal was to produce this data every quarter.
The institution transferred the website URLs of the 1.2 million companies to Milda via an API.
A series of targeted keyword searches were performed.
Milda automatically enriched the data, identifying companies involved in the specified niche technologies and categorising them by industry and activity type.
The platform extracted data on investment announcements and linked it to the companies' products, technologies, and locations.
About 2/3 of the companies were from non-English speaking regions (e.g., France, Germany, BRICs, and emerging markets), so Milda machine-translated the data from 30 different languages into English
Within three days, Milda enriched the data for 1.02 million companies, achieving 85% coverage.
The remaining companies were mostly low-quality or had non-functional websites.
Detail
Milda provided in-depth insights into the investment gaps and strengths of clean and renewable energy companies across different regions, far surpassing the detail offered by other sources.
Speed of delivery
The enriched investment data, which did not previously exist, was delivered to the client within three days.
Cost-effectiveness
Unlike other sources that focus only on large multinationals or patenting companies and often come with high costs, Milda provided comprehensive, detailed data at a more accessible price point.
This case study highlights how Milda.ai can efficiently and cost-effectively enrich massive datasets, providing valuable insights into niche markets like clean and renewable energy technologies.
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