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Valnox Labs · Reference architectures

Transparent reference systems designed around real operational problems.

The work below is not client work. Each Valnox Labs reference architecture exists to make data, model, integration, and operational decisions tangible.

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VALNOX LABS

System connecting enterprise data sources to a secure RAG assistant01

Enterprise Knowledge System

Reference architecture · Not a client case study
RAGPrivate AIEvaluation

Unifying fragmented enterprise knowledge in one cited AI assistant

A RAG architecture connecting PDFs, wikis, tickets, and product documentation through permission-aware retrieval and citation.

Reference scenario

In this reference scenario, knowledge is fragmented across systems and users must search multiple sources for a current answer.

Architecture approach

The reference architecture combines source normalization, access controls, hybrid search, and reranking in one retrieval layer.

System design

Ingestion, metadata, permission filtering, retrieval, reranking, the LLM, citations, and feedback are designed as one observable flow.

Target system qualities

Cited-answer design

Permission-aware access

Retrieval quality measurable with an evaluation set

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Computer vision system inspecting a metal part on a production line02

Manufacturing Quality System

Reference architecture · Not a client case study
Computer VisionEdge AIManufacturing

Detecting manufacturing defects in real time with computer vision

A visual inspection system combining camera integration, defect segmentation, edge inference, and quality operations.

Reference scenario

In this reference scenario, manual inspection is inconsistent and small surface defects may be missed at production speed.

Architecture approach

The reference architecture combines lighting and camera standards, controlled labeling, and low-latency inference at the edge.

System design

Cameras, model inference, PLC signals, alerts, and human feedback are designed as one quality loop.

Target system qualities

Real-time defect-alert design

Traceable quality records

A feedback loop for new defect classes

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Platform connecting LLM application components to a central operations layer03

AI Operations Platform

Reference architecture · Not a client case study
LLMOpsObservabilityCI/CD

Operating LLM applications through one observable production platform

A platform combining model routing, prompt versioning, evaluation, caching, tracing, and CI/CD in one operational control plane.

Reference scenario

In this reference scenario, the effect of prompt and model changes on quality, latency, and cost is not visible.

Architecture approach

The reference architecture defines a controlled release flow that links each version to datasets, evaluation results, latency, and cost metrics.

System design

Gateway, registry, evaluation, tracing, caching, guardrails, and deployment are designed around one control layer.

Target system qualities

Measurable version comparison

Safer releases and rollback

Application-level cost visibility

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VALNOX / LABS

What is Valnox Labs?

Valnox Labs work consists of non-client reference architectures created to demonstrate our technical approach. They do not claim a real client, delivered engagement, verified outcome, or client metric.

VALNOX / PROJECTS

Let’s adapt this reference approach to your operation.

We will assess your process, data, and success criteria to design the smallest meaningful production scope together.

Tell us about your project
Direct email
info@valnox.ai
Location
Bilişim Vadisi, Gebze/Kocaeli, Türkiye
Delivery model
Founder-led, end-to-end