About INSYTES
Make industrial decision-making trustworthy.
INSYTES exists to help industrial teams move beyond intuition, correlation, and trial-and-error, toward decisions grounded in clear cause-and-effect understanding.
What We Do
INSYTES is a deep-tech company building causal AI solutions for industrial efficiency.
Our flagship product, Cauza, brings causal discovery and decision intelligence into an accessible, no-code platform for industry.
Our Origins
INSYTES was born at the intersection of academic research and real industrial challenges.
The core technology behind Cauza originates from doctoral research in causal AI and decision intelligence, developed and validated in collaboration with universities and industrial partners.
Science
Relevance
Impact
Scientific Foundation
INSYTES is grounded in peer-reviewed research, not experimentation by trial.
Doctoral research in causal discovery and explainable AI
Multiple academic publications across energy, logistics, and manufacturing
Continuous collaboration with research institutions
This ensures our methods are transparent, auditable, and reliable in real-world systems.
Team
INSYTES is driven by a small, focused team combining deep technical expertise with industrial understanding.

Karim Abualrish
Co-Founder
Leads venture building, business development, and strategic partnerships. Bridges research-driven technology with operational execution.
Connect on LinkedInHover over a node to learn more about each team member
Ecosystem & Support
INSYTES is part of a strong innovation and research ecosystem.
These institutions support INSYTES through funding, mentorship, infrastructure, and long-term collaboration.
Our Philosophy
We believe industrial AI must be:
Explainable
Decisions must be understood, not guessed
Auditable
Insights must be defensible
Practical
Value must be measurable
Responsible
Aligned with EU AI governance and ethics
Technology should reduce uncertainty, not create more of it.
Looking Ahead
INSYTES is continuing to expand its causal AI platform through ongoing research and development, pilot projects with industrial partners, and collaboration across academia and industry.
Our goal is simple: turn complex data into clarity that teams can trust.