XTRACTIS®
the Reasoning AI for Trusted Decisions by design
automatic knowledge extraction from data

Cutting-Edge No-Code General-Purpose Efficient Augmented Cognitive Knowledge Based Data Driven Augmented Symbolic Continuous Logics Based White-Box Models Generator AI-ACT Compliant
artificial intelligence
Powerful
general-purpose AI
From data, XTRACTIS automatically discovers models of complex behavior in various domains. This can be human decisions, natural phenomena, or artificial processes, like control of autonomous devices.
XTRACTIS-induced models are ready-to-use offline or embedded, for prediction in real-time and optimization.



To accomplish this challenge, our technology reproduces human induction to find relevant knowledge from observations as in experimental sciences. It also implements the other 2 modes of reasoning: Deduction and Abduction, to easily put this knowledge into use.
Reliable white-box AI systems
XTRACTIS models are robust: their performance is higher than mainstream AI techs, as benchmarks prove.
Models are also intelligible: humans are able to fully understand the internal decision-making logic of the AI systems.
Experts can validate their models before pushing to end-use, or audit them before submission to certification to comply with AI regulations for high-risk applications.

Our algorithms are based on the mathematical theory of Fuzzy Relations of order N: fuzzy logic is more consistent with real-world data than binary logic without loosing human understanding. Our solution also implements Collective and Evolving Learning algorithms to obtain models having the highest possible performance.
High-performance
Easy-to-use
AI Platform
XTRACTIS comes in a no-code, feature-rich, all-in-one software platform accessible on a secure private cloud or on-premise servers.
Multiple Predictive Applications
As XTRACTIS is a Trusted General-Purpose AI, you can use it in any sector to:
★ Automate complex decision processes to make them systematic, more objective, and more reliable.
★ Optimize automated decisions to increase effectiveness, pro-activity, availability, productivity, and profitability.
★ Secure decision-making support by using transparent models, to minimize risks when decisions are critical.
★ Embed automated decision systems in autonomous devices after their audit and certification.
Whatever you application, you always trust the XTRACTIS-deduced decisions thanks to the Robustness and Intelligibility of your models.
Predictive Personalized Holistic Medicine: metabolic, epigenetic, physiological, pathological. Patient surveillance, Virtual Screening, Protein Homology, Toxicity, Drug Discovery, Health Insurance Risk Management...
Autonomous Systems, Collaborative Devices, Command & Control, Malicious Activity Detection, Surveillance, Cybersecurity...
Product Design & Ergonomics, Sensory Marketing & Engineering, Smart Industry, Quality Control, Maintenance & Diagnosis, Logistics, Risk Analysis, Environment, Geomatics, Optimization, ADAS, Autonomous Vehicles...
Scoring and risk analysis, Econometrics, Malicious activities, Venture capital, Behavioral finance, Wealth management, Real estate finance, Strategy, Marketing & CRM, Customer behavior (appetence, attrition, emotions), HR, Legal...
Best Accuracy and Intelligibility
Our 17 public Use Cases on real data include comprehensive benchmarks against Neural Networks, Boosted Trees, Random Forests, and Logistic Regression.
Click on a slide to access the corresponding study.
No-Code All-in-One AI Platform
Induction Robots
Discover your process rules from data and understand how it behaves, thanks to XTRACTIS GENERATE
Deduction Robots
Make real-time predictions at high-frequency for new input situations using your models with XTRACTIS PREDICT
Abduction Robots
Automatically invert your models to discover the most optimal solutions in no time with XTRACTIS OPTIMIZE
Supervision Engine
Let XTRACTIS MONITOR supervise the quality of your deployed models to take action when they expire

Prof. Zyed ZALILA
CEO-founder, Intellitech
They have trusted XTRACTIS






























