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Depixen Tech Stack

AI-powered product libraries for construction using semantic data and vision models

Information Technology & Services London 11–50 employees Founded 2008 Privately Held

Depixen builds autonomous product libraries for the construction ecosystem using PyTorch, TensorFlow, and vision models (YOLO, Detectron2, Vision Transformer) paired with semantic technologies (SPARQL, knowledge graphs). The tech stack reveals a dual focus: computer vision for product perception and linked-data systems for ecosystem coordination. Active hiring is senior-heavy (7 of 9 roles) across engineering and data, concentrated in Turkey, while projects span ML-driven classification, payment infrastructure, and semantic search — suggesting both technical depth and operational complexity as they scale.

Tech Stack 35 technologies

Core StackPyTorch TensorFlow Python Docker Kubernetes MLflow Weights & Biases AWS Go Java PostgreSQL Redis React Figma GitHub Actions GitLab CI/CD Jenkins Swift GCP Azure TensorRT OpenVINO ONNX Runtime YOLO Detectron2 Vision Transformer SPARQL SQL Git iOS+4 more

AdoptingCLIP

What Depixen Is Building

◆Challenges

Ensuring high availability for millions of transactions
Scaling payment processing infrastructure
Compliance with pci dss and psd2
Scalable and reliable infrastructure systems
Maintaining system reliability
Fragmented data
Static catalogs
Data labeling for ml

▲Active Projects

Payment and wallet services development
Payment processing infrastructure
Next-generation perception systems
Semantic data systems: ontologies, knowledge graphs, and metadata frameworks
Machine learning models leveraging knowledge graphs for recommendation and classification
Digital wallet infrastructure
High-availability systems
Autonomous product libraries
Data-driven revenue models
Semantic search capabilities

Hiring Activity

Accelerating9 roles · 4 in 30d

Department

Engineering

6

Data

2

Product

1

Seniority

Senior

7

Mid

2

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About Depixen

Depixen is a London-based AI and construction-software company founded in 2008. The company designs autonomous product libraries that aggregate data from the construction supply chain — over 200 manufacturers and 100+ architects, designers, and consultants — using semantic technologies aligned with W3C standards. Their platform combines computer vision for product recognition with knowledge graphs and ontologies to create a unified, machine-readable view of construction products and their properties. Revenue streams include payment and wallet services alongside data-driven licensing models. The 11–50 person team is engineering-led, with active hiring in senior technical roles.

HeadquartersLondon

Company Size11–50 employees

Founded2008

Hiring MarketsTurkey

Frequently Asked Questions

What AI and ML technologies does Depixen use?

PyTorch, TensorFlow, YOLO, Detectron2, Vision Transformer, MLflow, Weights & Biases, and SPARQL for semantic reasoning. The company is adopting CLIP for vision-language alignment.

What is Depixen working on?

Autonomous product libraries, next-generation perception systems, semantic data frameworks (ontologies, knowledge graphs), ML-driven product classification, payment infrastructure, and semantic search capabilities for the construction ecosystem.