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Home Market Research Startups

Copenhagen’s amass raises €1.4M to build an applicable AI map of the world’s scientific knowledge

by TheAdviserMagazine
2 months ago
in Startups
Reading Time: 2 mins read
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Copenhagen’s amass raises €1.4M to build an applicable AI map of the world’s scientific knowledge
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Danish startup amass raised funding from various investors to build the ‘intelligence layer for life-science workflows. However, the process behind it is not so simple. Read below to know more.

Contentlockr

Copenhagen-based amass, a scientific intelligence platform for life sciences, has secured €1.4M funding from Giant Ventures, Kost Capital, EIFO, and Christian Thirion, who also becomes the company’s Chairman. 

In addition to funding, the Danish company also announced the appointment of Tommy Ahlers (former Minister for Science, Technology, Information and Higher Education in Denmark) and Bodil Sidén (Kost Capital) to the board. 

With new funding, the company plans to improve its products and expand into more markets. 

The company will also use the capital to create an AI map that shows the world’s scientific knowledge, helping insights to last and lead to discoveries.

amass: Scientific intelligence platform

Typically, scientific knowledge powers the world’s discoveries, but all too often, the findings are inaccessible, hard to reference, and siloed. This slows down the next breakthrough idea. 

Here’s where amass comes into play

Founded by Henrik Jensen (CEO) and Alexander Junge (CTO), amass offers a platform that connects patents, research papers, regulatory filings, trial data, and internal documents to help researchers make quicker decisions. 

The company is on a mission to help pharma and biotech teams get to discoveries quicker — building an intelligence layer for life science workflows. 

Instead of finding information, the platform links concepts from different sources and shows the evidence behind each result, supporting transparency and decision-making in regulated fields.

The company develops specialised models to capture important scientific details and minimise irrelevant information in complex queries. 

At present, the company’s early users include startups, public institutions, and industry players. 



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Tags: 1.4MamassapplicableBuildCopenhagensKnowledgemapRaisesScientificWorlds
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