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Hiasynth raises angel funding to build a queryable synthetic model of Europe’s population

AI startup Hiasynth has raised an angel funding round led by Further Than Capital. The company has built a synthetic model of Europe's population at 1:1 scale, designed to be queried by AI. With it, a...

Hiasynth raises angel funding to build a queryable synthetic model of Europe’s population

AI startup Hiasynth has successfully raised an angel funding round led by Further Than Capital. The company has created a synthetic model of Europe's population at a 1:1 scale, which can be queried by AI. This innovative model allows any company to analyze consumer markets across Europe. With the model, half a billion personas from 37 countries are available, each with over 600 attributes that accurately represent the real population's behavior.

Each persona's lifestyle, including income, housing, consumption, habits, and values, is determined by their living conditions, making the consumption patterns realistic. Emma Agering, the founder of Hiasynth, explains that Europe has never behaved like a single market due to differences in language, consumption patterns, and research needs.

Consequently, many European companies have expanded to the US before neighboring countries. The angel funding round, led by Further Than Capital, will be used for the launch and product development of Hiasynth's model. The investment aims to support founders before ideas, as Emma Agering has prior experience in building successful startups.

The company plans to launch in September 2026 at Bits & Pretzels in Munich, Germany, and will be accessible through the MCP (Model Context Protocol) standard, enabling AI assistants like Claude and ChatGPT to query external tools and data directly. Stefan Lindeberg, Further Than Capital and co-founder of Creandum, highlights that Hiasynth replaces guesswork with actual population data, allowing AI to provide actionable insights instead of just sounding convincing.

Written by urgent.news from Tech.eu's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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