Intelligent systems for complex networks

Qira builds AI-powered platforms that model, monitor, and optimize the behavior of large-scale networks in real time.

Explore Our Work

Three platforms, one framework

Every product is built on the same network coordination framework — mathematical physics applied to real-world complexity.

Active Research

Expression-Gated Cognition

An empirical study of how emotional expression modulates cognitive performance. Validated across 58 subjects with a novel gating function that separates compressors, expanders, and suppressors — with a university collaboration pending.

N = 58
Subjects
r = 0.311
Pearson correlation
3 types
Expression profiles
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In Development

Language-Optimized Learning Model

A custom 5-stream hybrid Transformer-SSM language model with adaptive training dynamics. Backed by a Google TRC grant for TPU v4-32 pod access, applying network physics to the training process itself.

5-stream
Hybrid architecture
TPU v4-32
Google TRC grant
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Our approach

Qira's research centers on a unifying insight: the same mathematical structures that govern phase transitions in physical networks also describe critical behavior in traffic systems, cognitive processes, and language model training dynamics.

The same framework that detects freeway congestion cascades also identifies structural instability in codebases and predicts phase transitions in language model training. This is not analogy — it is the same mathematics applied at different scales.

By grounding each product in network coordination theory rather than domain-specific heuristics, we achieve generalization that pure machine learning cannot. Our models do not merely fit data — they capture the dynamics that generate the data.

Network Physics

Mathematical modeling of how information, congestion, and instability propagate through connected systems.

Real-Time Inference

Continuous monitoring loops that detect anomalies and predict state changes before they cascade.

Cross-Domain Transfer

A single theoretical framework applied to transportation, cognition, and language — validated empirically in each domain.

Who we are

Bryan Leonard

Co-Founder & Lead Researcher

Systems architect and applied researcher responsible for platform engineering, data infrastructure, and empirical validation. View Portfolio →

Leads the design and deployment of Qira's live monitoring systems and manages all computational research programs.

Brandyn Leonard

Co-Founder & Theoretical Framework

Originator of the core gating functions and boundary conditions that underpin Qira's network coordination theory. View Portfolio →

Responsible for the mathematical architecture connecting traffic dynamics, cognitive modeling, and adaptive training theory.

Work with us

Get in touch

We partner with transportation agencies, research institutions, and technology teams that need rigorous, real-time intelligence for complex systems.

Email
bryanleonard@imagineqira.com
brandynleonard@imagineqira.com

Phone
(480) 256-9684