Understand
EvoQ™,
The oxide Core AI Engine
A unified AI core where learning, reasoning and adaptation converge, designed to evolve with the real world.
It transforms data and objectives into adaptive intelligence that understands context, explains its logic and improves continuously.
EvoQ Architecture
The Core of Integrated Intelligence
At the heart of Oxide’s technology stack, EvoQ functions as a self‑evolving intelligence core that unifies perception, abstraction and reasoning within a single architecture.
Rather than stacking pre‑trained models or APIs, it develops understanding through continuous feedback, interpreting information, refining its logic and adapting to realities.
Designed as a living system, EvoQ continuously restructures its knowledge and reasoning processes, maintaining coherence as it evolves.
This architecture enables what other frameworks cannot achieve: AI that learns from experience, explains its reasoning and grows with its environment.
Objective-Driven Reasoning Agents
Built on top EvoQ’s core, specialized reasoning agents combine real‑time perception with goal‑oriented inference. They operate within defined objectives, continuously optimizing decisions and outcomes, tackling complex, high‑value challenges across finance, healthcare and digital commerce.
Unified Intelligence, Not Fragmented Models
EvoQ replaces disconnected ML libraries and multiple LLM APIs with a coherent, self‑contained AI core focused on the representation of intelligence itself, not just incremental improvements.
This unified foundation delivers deeper consistency, interoperability and scalability across cognitive functions.
For Real-World Evolving Complexity
Oxide's core AI technology integrates inductive inference (such as LLMs and Deep Learning), formal reasoning and neurosymbolic AI into a feedback- driven architecture.
Through continuous self‑optimization, EvoQ dynamically refines its internal models, achieving adaptive precision in environments that demand real‑time learning and contextual understanding.
Core Principles of the System
EvoQ is a framework for building intelligence that’s explainable, structured and fast. Each layer of its architecture is guided by core principles that ensure transparency, reliability and performance in complex real‑world environments.
Neuro-Symbolic AI
Neuro-symbolic reasoning combines the intuitive pattern recognition of neural networks with the precise logical and computational reasoning of symbolic AI systems. This integrated approach enhances the understanding and interpretation of complex data, also allowing for the enforcement of specific constraints and policies in the outputs. It enables AI to recognize patterns, learn from large datasets, and execute complex plans based on predefined goals, all while adhering to corporate guidelines. Additionally, the system performs analytical operations, logically aggregates and selects insights, presents diverse decision options, and generates human-readable explanations.
Explainable And Transparent AI
Critical decisions in the real world rely on explainable and transparent insights grounded in facts and evidence. Clear explanations and data transparency complement reasoning, providing a solid rationale for decisions. In Oxide's AI system, comprehensive explanations enhance accuracy and precision, and play a key role in improving reasoning capabilities. This approach benefits both the training of generative AI models and the direct improvement of computational reasoning models.
Isolation For Control
Oxide’s AI system draws inspiration from biological processes, where the brain isolates selections of learned models based on specific information and trajectories. This isolation is crucial to address data errors, interpretative ambiguities, contradictions, and manipulations in real-world scenarios. Similarly, all AI agents in Oxide's system are isolated, along with the environments in which they operate, ensuring robust and reliable performance.
The Need For Speed
Algorithmic innovation significantly influences the cost and efficiency of frontier AI, with a single breakthrough potentially redefining hardware and software needs. Oxide AI develops hybrid systems that utilize generative AI for natural language tasks and computational AI for exponentially faster numerical processing. This approach not only provides a competitive edge but also supports environmental sustainability.