Building Computational AI Infrastructure.
itriX advances Computational Infrastructure for the AI era through mathematical innovation, turning original research on mathematical representation and computational structure into products and industrial value.
Discovering new value in mathematics.
As enterprise AI use grows, repeated AI calls, compute load, memory and power use, and operating costs matter more. AI is now judged on efficiency and economics as well as performance. itriX examines what AI systems observe, when they decide, and how they compute — then designs representations and execution that fit the problem’s mathematical structure.
Examine what AI systems observe and when they decide.
Design representations that fit the problem’s mathematical structure.
Find efficiency gains through execution that matches that structure.
ASTOP
Cuts the cost of AI repetition.
AI Observation & Execution Optimization. Built on PRISM to cut repeated observation and unnecessary AI decision requests in existing agent and automation workflows.
What brings you to itriX?
Tell us why you’re here and we’ll point you to the right information and next step.
From observation to execution.
ASTOP addresses efficient observation and inference control driven by state changes; the AXIOM family covers the structural representation and implementation of tensor operations; and QNTA covers a neural network training architecture and runtime built on inference operations.
Mathematical Intelligence
Mathematical Intelligence is itriX’s technology philosophy: we research and develop technologies that raise the efficiency of observation, computation, and learning by analyzing and re-representing mathematical structure. The technologies below underpin our products.
Connecting mathematical research to industrial technology.
itriX develops core technologies grounded in mathematical research and is building its Intellectual Property. Our research and commercialization team connects mathematical research, core technology development, and customer application.
Leads math-based research direction and commercialization.
Redesigning the future of AI through mathematical innovation.
Hello,
I am Myungjoo Kang, CEO of itriX.
Artificial intelligence is rapidly transforming our society and every industry. Yet as AI advances, it demands ever greater computing resources and energy, and the efficiency and reliability of computation are becoming the key challenge that will determine whether AI can keep developing sustainably.
I believe the answer to this challenge lies not simply in more computation, but in mathematical innovation that looks at the principles of computation in a new way.
itriX is a math-based deep-tech company founded on this belief.
We aim to go beyond improving existing technologies and to redesign the very way problems are represented and computed. Building on mathematical insight, we are creating next-generation Computational AI Infrastructure that reduces the cost and complexity of AI computation and delivers higher performance and reliability with limited resources.
To this end, we are researching our own core technologies — from technologies that optimize how AI observes and executes, to innovations in computational structure, efficient AI training, and new numerical computing methods for Physical AI.
Our goal is not simply to make AI faster. It is to open a future in which AI is more efficient, more trustworthy, and usable by more people.
To make this happen, itriX pursues both the depth of mathematical theory and the practicality of real-world industry. We will focus on turning academic discoveries into real technologies, verifying their value objectively, and solving the hard problems that our customers and industries face.
Going forward, AI will do more than drive innovation in science, technology, and industry — it will widen the very range of problems humanity can solve. At the center of this change, itriX aims to grow into a technology company that moves beyond the limits of conventional computation and opens up new possibilities.
Discovering new principles in mathematics, realizing new possibilities through technology, and building a better future through innovation —
this is the value itriX pursues and our promise for the future.
Thank you.
Myungjoo Kang, CEO, itriXBuilding industry deployments and core research side by side.
CORE TECHNOLOGY VALIDATION
- PoC · ValidationJudge-CIA · Multi-AI decision reliability
Validating multi-AI decisions, error-independence analysis and decision reliability through PoCs with WISEWIRES and the financial sector
- Program development · Pilot preparationPRISM / ASTOP · AI execution optimization
Research on call-control and caching to cut unnecessary repeated AI calls, and development of the installable ASTOP program
- Hardware PoC validationQNTA · Edge AI training
Technology validation on DEEPX NPUs, and reproduction of the training path in the DLA + CPU environment of NVIDIA Jetson AGX Orin
- PoC · Optimization validationAXIOM Tensor · AI computation structure optimization
Validating whether structural re-representation of tensors and matrices can improve computational efficiency, and optimization
INDUSTRY PROJECTS
- Development · DeliveryInsurance licensing exam item-generation AI
Item-generation workflow system with expert review and approval built in
- PoC · ValidationFinancial mis-selling detection AI
Checks for possible breaches of sales-conversation rules using rules, evidence and multiple AI judgments
- Applied developmentMathGen · Ad-creation AI
Helps teachers write and review math items; creates content that follows brand guidelines
- Planning · ResearchK-EDA electronic design AI
Reviewing an R&D roadmap for automating PCB/ECAD placement, routing and rule checks
Building the future of Computational Infrastructure together.
We select the customer’s key AI and computing challenges and set measurable goals and validation criteria. Based on actual validation results, we discuss scope, partnership, and Licensing terms.
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