kausable

📂 Artificial Intelligence📍 Heidelberg🗓️ Founded: 2025

A Heidelberg AI lab founded in 2025 researching alternatives to repeated model retraining, developing systems grounded in cause-and-effect relationships and synthetic causal data.

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Podcast Episode

🎙️ Deep Dive

telli, kausable, Yope — $15M for AI agents, €12M for adaptive models and $12.3M for private social — Daily News July 23, 2026

Listen to the episode

About kausable

kausable was founded in 2025 in Heidelberg by Johannes Haux (CEO), Dr. Benjamin Herdeanu and Gregor Ramien, with the goal of rethinking how AI models learn and adapt. Continuous retraining makes many AI systems expensive and inflexible when environments change: kausable develops models grounded in cause-and-effect relationships and synthetic causal data to build systems that understand how environments change and apply knowledge to unfamiliar situations from a limited number of examples. With a team of 9, the startup closed a €12M seed round in July 2026, led by UVC Partners and Entourage, with participation from HTGF (High-Tech Gründerfonds) and Mätch VC. The funds will be used to expand the team, develop the models further and validate them with initial industrial customers in sectors including robotics, industrial systems, forecasting and healthcare. Synthetic causal data could reduce dependence on large historical datasets — one of the fundamental bottlenecks in developing adaptive AI.

The Story

Founded in 2025 in Heidelberg by Johannes Haux, Dr. Benjamin Herdeanu and Gregor Ramien to develop causal and adaptive AI.

How kausable works

Business Model

Development and future B2B commercialisation of foundation models and vertical applications; licensing and APIs.

Revenue Model

Licensing, APIs or industrial collaborations; the final commercial model has not been disclosed.

Products & Services

Key Products

  • Reasoning-first frontier AI models
  • Causal world models

Core Use Cases

  • Robotics
  • Industrial systems
  • Forecasting
  • Healthcare
  • Model adaptation to new contexts

Market & Clients

Key Customers

Early pilot companies in industrial systems, robotics, forecasting and healthcare; names have not been disclosed.

Geographic Presence

DE

How kausable competes

Competitive Advantages

  • Cause-and-effect modelling approach — alternative to continuous fine-tuning
  • Adaptation to new contexts from limited examples
  • Synthetic causal data: reduces dependence on large historical datasets

How kausable grows

Growth Strategy

Expand the team, develop the models and validate them with initial industrial customers.

Distribution Model

Research partnerships, pilot projects and future distribution through licensing or APIs.

Moat (Defensibility)

Intellectual property on causal research, proprietary synthetic data and the team's scientific expertise.

Regulatory Context

European applications will be subject to the AI Act and to sector-specific rules for the use cases involved (healthcare, industrial).

Key Risks

  • Technology remains research-stage — production transfer not yet demonstrated
  • Generalisation challenges outside laboratory settings
  • High compute requirements
  • Competition from major AI laboratories with superior resources

Strategic Insights

  • Synthetic causal data could reduce dependence on large historical datasets.
  • The decisive test will be demonstrating adaptation in real industrial applications outside the laboratory.

Funding & Investors

Total Funding

€12M

Funding Rounds

  • - Seed: 12000000
    Lead: UVC Partners

Key Investors

UVC PartnersEntourageHTGFMätch VC

Founding Team

Founders

Johannes HauxCo-founder & CEO
Dr. Benjamin HerdeanuCo-founder
Gregor RamienCo-founder

Key Metrics

Seed round€12M (2026)
Team size9 (2026)

Lessons from kausable

  • A strong scientific thesis should be connected early to measurable use cases.
  • Fundamental research requires patient capital and technically capable investors: HTGF and UVC Partners are coherent profiles.

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Sources

🎙️ Scalable Podcast — European startup stories · 🇮🇹 in Italian
Spotify 🎧 Apple