Gini extracts structured data from unstructured documents using self-developed AI (PyTorch, Hugging Face, vLLM) and packages it into payment experiences for banks, insurers, and e-commerce platforms. The tech stack—heavy on ML infrastructure (Kubeflow, MLflow, Weights & Biases) paired with computer vision (OpenCV, Pillow)—reflects a company betting on document-understanding as core IP rather than bolted-on. Current hiring is sales-forward (5 roles) with emerging data science velocity, suggesting a shift from pure product maturity toward go-to-market scale.
Gini, founded in 2011 and headquartered in Munich, is a fintech company specializing in AI-driven document extraction and mobile payment solutions. The core product—Photo Payment—is embedded in major German banks' apps (Deutsche Bank, Commerzbank, Sparkassen, and others), enabling customers to photograph and submit payment documents instead of manual data entry. Gini Pay Connect extends this to insurance workflows, connecting health insurer apps with banking infrastructure for streamlined claims and payments. The company operates as a B2B payments and data-extraction platform serving three verticals: banking, insurance, and e-commerce.
Self-developed AI for extracting structured information from unstructured documents in real-time. The stack includes PyTorch, Hugging Face Transformers, vLLM, OpenCV, and ML ops tools (Kubeflow, MLflow, Weights & Biases).
Munich, Bavaria, Germany. All current hiring is in Germany.
Gini's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.