Brilliant, Scalable and Effective

Agent-oriented AI for supply chains, consumer finance, and personalization

Bring brilliance to your supply chain!

Aleph agents augment the intelligence and reach of your day-to-day operations to face new business challenges.

With our proprietary machine reasoning technology and our state-of-the-art machine learning and mathematical optimization platform, you will be able to outgrow your business limitations and inventory distortions, securing the visibility, adaptability and personalized attention that customers expect.

Supply chain optimization
Take care of demand fluctuations, opacity, and the increased size, complexity and dynamics of supply networks.

Consumer finance
Boost growth and margins with our individualized behavioral modeling and risk management technology.

Bring clients and other business actors to center stage, maximizing service and customer satisfaction.

Significantly improve supply chain key metrics

OTIF Service Rate Increase
Inter-warehouse inventory movements savings
Before Aleph: 178,090 CS
After Aleph: 134,703 CS
Risk reduction for next 10 days
Manual Revisions Required Before Aleph: 46.85%
Manual Revisions Required After Aleph: 24.62%
Transport capacity risks avoided
Over Capacity Before Aleph: 58 Embarkment Units
Over Capacity After Aleph: 48 Embarkment Units

Symbiosis Unleashed: Amplifying AI with the Integration of Logic and Generative Large Language Models

As we delve deeper into the AI era, we are confronted with a growing need for supporting software solutions to real-world business and engineering problems. In response to this need, we propose the marriage of formal logic, particularly a new innovative modal logic called Aleph, with generative Large Language Models (LLMs).

We endow software with considerate, reliable, and intelligent agents of people’s interests, beliefs, and behaviors.
We offer high-value cloud software solutions that integrate reasoning, learning, and optimization algorithms for solving highly complex commercial and scientific problems using digital agents to complement human capabilities.


The human ability to solve problems by attributing mental states and intelligence to oneself and to others, namely agent capabilities, is the result of a long but highly successful evolutionary process. By augmenting this ability with mechanical methods, new far-reaching solutions can be attained.