Research

nextX AG is rooted in research. Our focus lies in developing novel technologies at the intersection of physics and artificial intelligence.

RESEARCH IS OUR CORE

Our Focus

Fundamental Research

We explore new theoretical approaches beyond classical neural networks

Physics-Based AI

Deterministic methods from theoretical physics for reliable, auditable systems

Applied Research

Transferring research results into production-ready systems

Our Spectrum

Our research spans the entire technology stack:

Hardware

Sensor technology, electronics, embedded systems, energy and power systems

Drive Systems

Actuators, motor control, motion systems

Robotics

Autonomous systems, control, human-machine interaction

IoT

Connected devices, edge computing, data acquisition

Software

AI systems, data analysis, backend infrastructure

Collaborations

We believe in open collaboration. nextX AG actively partners with universities, research institutions, and industry partners – from exploratory fundamental research to joint product development.

Interested in a collaboration? We welcome inquiries from academia and industry.

"Research is not a by-product – it is our core."

— nextX AG Philosophy

15
Research Papers
6
Published
7
Patents Filed
CC BY 4.0
Open Access

Publications

Our published research and working papers.

PUBLISHED2026-02

The Fine-Structure Constant from Discrete Hodge Theory

Sayed Amir Karim

This paper derives the electromagnetic fine-structure constant α⁻¹ = 137.0359 (0.79 ppm deviation) from the nilpotency condition d²=0 via discrete Hodge theory. The derivation uses a self-dual triangulation (K₄), the Pell equation from circulant criticality at z=4, and the Koide phase δ=2/9. No free parameters are fitted; all values emerge from mathematical structure.

Precision
0.79 ppm
α⁻¹
137.0359
Parameters
0 free
Mathematical PhysicsView Details →
PUBLISHED2026-02

The Pell Equation from Circulant Criticality (z=4)

Sayed Amir Karim

A mathematical note isolating the number-theoretic step used in the AQEA chain: how criticality of the z×z circulant at z=4 forces the amplitude A²=2, introducing the quadratic field Q(√2). The Pell equation x²−2y²=1 then uniquely selects (N,d)=(3,2), producing the stability parameter δ=d/N²=2/9.

Critical z
4
Pell (N,d)
(3,2)
δ
2/9
Mathematical TheoryView Details →
PUBLISHED2026-01

AQEA: Technical Report — Domain-Adaptive Semantic Compression of Embeddings

Sayed Amir Karim

Technical report introducing AQEA compression achieving up to 320×+ compression with ≤97% quality retention across four modalities (Video, Text, Audio, Protein). Features steerable 'Lenses' (~35KB) for domain adaptation without retraining the underlying embedding model. Validated with ground-truth human labels [GT-H].

Compression
320×+
Quality
≤97%
Modalities
4
Information TheoryView Details →
PUBLISHED2026-01

Addressing the Semantic Twins Problem in Legal RAG: A Lens Steering Approach

Sayed Amir Karim

Working paper addressing the 'semantic twins' problem in legal RAG systems, where documents with identical embeddings carry opposite legal weight. The Lens steering approach achieves Hard-Negative@10 (HN@10) reduction from ~56% to 0.000, demonstrating complete resolution of the semantic collision problem.

HN@10 Before
~56%
HN@10 After
0.000
Reduction
100%
Ethics & SecurityView Details →
PUBLISHED2026-01

Ground-Truth-Aware Metric Terminology for Vector Retrieval

Sayed Amir Karim

A proposal for disambiguating evaluation in embedding-based systems through terminology standards. Introduces notation requiring explicit ground-truth encoding: [GT-H] for human labels, [GT-S] for synthetic, [GT-M] for model-generated. Argues that metrics like Spearman correlation, Recall@k, and nDCG are meaningless without ground-truth specification.

Standard
GT-*
Types
H/S/M
Adoption
Proposed
Semantic SystemsView Details →
PUBLISHED2025-01

Multi-Layer Network Theory Resolves the Semantic Compression Problem

Sayed Amir Karim

Semantic similarity systems face a fundamental trade-off between domain expertise and multilingual capability. This work presents a novel three-layer semantic approach that integrates domain-specific, cross-linguistic, and cross-domain embeddings, achieving 15% higher correlation than existing methods.

Correlation
r = 0.831
Concepts
783K
Improvement
+15%
Network TheoryView Details →
CONFIDENTIAL2024-12

AQEA Universal Addressing: 4-Byte Knowledge Representation

Sayed Amir Karim

Introduction of the AQEA Universal Addressing system, demonstrating how any concept in any language can be represented using just 4 bytes (AA:QQ:EE:A2 format). This breakthrough enables unprecedented compression and retrieval performance through natural information organization patterns.

Address Size
4 bytes
Concepts
Languages
Universal
Information TheoryView Details →
CONFIDENTIAL2024-11

Harmonic Hierarchies in Knowledge Graph Construction

Sayed Amir Karim

Application of golden ratio-based harmonic structures in building self-organizing knowledge graphs. This approach enables cycle-safe navigation through complex conceptual spaces while maintaining mathematical elegance.

Harmonic Ratio
φ (1.618)
Complexity
O(log n)
Safety
Cycle-free
Graph TheoryView Details →
CONFIDENTIAL2024-10

Ethical Constraints in Distributed Systems: RuleCore™ Architecture

Sayed Amir Karim

Introduction of RuleCore™, an immutable ethics enforcement layer that operates across distributed systems without central authority. The system uses cryptographic consensus to ensure ethical compliance that cannot be overridden.

Violations
0
Compliance
100%
Latency
0ms
Ethics & SecurityView Details →
CONFIDENTIAL2024-09

Phi Metrics: Measuring Information Integration in Complex Systems

Sayed Amir Karim

A mathematical framework for quantifying the degree of information integration in complex adaptive systems. Based on Integrated Information Theory, this metric provides objective measurement of system consciousness levels.

Φ Score
2.47
Correlation
87%
Speed
Real-time
Complexity ScienceView Details →
CONFIDENTIAL2024-08

Adversarial Robustness in Multi-Layer Networks

Sayed Amir Karim

Analysis of adversarial attack resistance in multi-layer network architectures. Demonstrates provable robustness guarantees with explicit Lipschitz constants.

Lipschitz
L=2.7
Resistance
99.9%
Defense
Certified
SecurityView Details →
CONFIDENTIAL2024-07

Universal Approximation in Semantic Spaces

Sayed Amir Karim

Proof of universal approximation capabilities in multi-dimensional semantic spaces with optimal convergence rates. Establishes theoretical foundation for arbitrary concept representation.

Approximation
O(n^-k/d)
Convergence
P=1
Bounds
Optimal
Mathematical TheoryView Details →
CONFIDENTIAL2024-06

Production Optimization for Quantum-Entangled Systems

Sayed Amir Karim

Optimization strategies for production deployment of quantum-entangled information systems. Addresses scalability, latency, and resource allocation in distributed environments.

Throughput
10K+ QPS
Scaling
Linear
Uptime
99.99%
System OptimizationView Details →
CONFIDENTIAL2024-05

Cross-Domain Semantic Bridging Theory

Sayed Amir Karim

Novel approach to connecting disparate knowledge domains through semantic bridging layers. Enables unprecedented cross-disciplinary knowledge transfer.

Domains
12
Preservation
87%
Speed
Real-time
Semantic SystemsView Details →
CONFIDENTIAL2024-04

Swarm Intelligence Integration Framework

Sayed Amir Karim

Framework for integrating swarm intelligence patterns into multi-layer network architectures. Enables emergent behavior while maintaining deterministic guarantees.

Agents
1000+
Behavior
Emergent
Outcomes
Deterministic
Distributed IntelligenceView Details →