Our work / Case study
A Language-Agnostic Intelligence Platform for International Market News and Trends
Market Intelligence
Context
What they needed
Heavy manual news monitoring across fragmented sources and languages, with slow and inconsistent analysis.
What we built
Ekohe built a platform that scrapes and aggregates international articles, with AI pipelines that summarize, classify and extract trends, and reports generated from curated sets. Manual news monitoring replaced by structured, filterable insight.
Details
Market and research teams monitored international news by hand. Sources were fragmented, articles arrived in several languages, and there was no structured way to extract insight from them. Analysis was slow, and its consistency depended on who did the reading.
The volume of news was not the core problem. The problem was that insight depended on manual reading, so coverage, speed and conclusions varied. The platform had to make the extraction consistent, while leaving interpretation to the people who know the markets.
Ekohe built a platform that scrapes and aggregates articles from multiple sources and languages. AI pipelines clean, summarize and classify each article, extract trends, and generate insights and reports. Teams work in an interface built around article cards, trends, collections and saved filters, and can share articles, export text and generate custom reports from any curated set.
Manual monitoring of news and markets is no longer needed. Teams understand their markets better through structured insight, assess risk more sharply and spot new opportunities earlier. Decisions rest on data rather than gut calls, and signals that used to stay buried in the volume of news now surface.
Articles are processed whatever their original language, so a market signal published in one language reaches teams working in another. The platform structures what was published; the analysts decide what it means.
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