Building AI Systems
That Earn Trust

NYRVEN combines research rigor with engineering execution. Our platform NyvLearn serves universities with hallucination-resistant AI — because reliability is not a feature, it is the foundation.

Founded February 2026 · Paris
Live ProductTrusted by Queen Mary University of London
4Academic Modules
3Agent Pipeline
0Hallucinations Tolerated

NyvLearn

Deployed

Academic RAG Platform

A multi-tenant platform that serves students with verified, citation-backed answers. Built on a 3-agent pipeline that retrieves, re-ranks, and validates every response before it reaches the user.

Too many AI systems are deployed without rigorous validation. NyvLearn brings structure, repeatability, and confidence to academic research assistance — making reliability measurable, not assumed.

Multi-tenant
Dedicated environments per university
3-Agent Pipeline
Retrieve → Re-rank → Validate
Structured Formatting
Verified answers with source citations
Hallucination Guard
Adversarial validation agent
NyvLearn — Academic Module

What are the key factors driving climate change and how do they interact with ocean circulation systems?

Overview: Anthropogenic greenhouse gas emissions are the primary driver, with CO₂ and methane leading radiative forcing [1].

Mechanism: Thermohaline circulation is sensitive to temperature and salinity changes, with Atlantic Meridional Overturning showing measurable decline [2].

Validated — 3 sources cited
Multi-Agent RAG
NyvLearn Engine

Capabilities Built for Serious Technical Work

We operate at the intersection of AI research, applied machine learning, and software engineering.

AI Research & Prototyping

Applied AI research with engineering rigor — from hypothesis to deployable prototype.

Intelligent Software Systems

End-to-end development of AI-powered applications built for reliability.

Model Validation Infrastructure

Structured frameworks for benchmarking and validating AI model outputs.

Applied ML Infrastructure

Scalable pipelines for data ingestion, training, inference, and monitoring.

Product Engineering

Technical product development from concept to launch with research-grade thinking.

Technical R&D

Exploratory research partnerships for technically ambitious problems.

Published Work

Peer-reviewed research on the intersection of agentic AI, software systems, and regulatory frameworks.

Technical/AI LawFebruary 2026

Mind The Gap: How the technical mechanisms of Agentic AI outpace global legal frameworks

An analysis of how agentic AI evolution is outpacing existing legal and regulatory frameworks.

Marcel Osmond & Thomas Jego (February 2026) · DOI: 10.5281/ZENODO.18777745

Read on Zenodo
TechnicalMarch 2026

A Critical Analysis and Reproducibility Study of Manifold-Constrained Hyper-Connections

Reproducibility and critical analysis of manifold-constrained hyper-connections in deep learning.

Thomas Jego (March 2026) · DOI: 10.5281/ZENODO.18852696

Read on Zenodo
LawMarch 2026

Trajectory-Based Liability: Regulating High-Capability Agentic AI in the 2026 Capability Frontier

Regulatory challenges and liability frameworks for high-capability agentic AI systems.

Marcel Osmond (March 2026) · DOI: 10.5281/zenodo.18828311

Read on Zenodo

A Process Built for Technical Rigor

01

Research & Scoping

Deep technical scoping to build the right system, not just a working one.

02

System Design

Architecture for long-term maintainability — modular, testable, evolvable.

03

Engineering & Validation

Rigorous implementation with continuous validation against real-world conditions.

04

Deployment & Iteration

Production delivery with structured feedback loops and performance monitoring.

Building Something Technically Ambitious?

Let's design it properly. Whether it's a research collaboration, a product demo, or a technical partnership — we're ready to engage.