Gini builds AI that reads unstructured financial documents and turns them into payment and claims workflows for German banks and health insurers. The stack pairs a Java/Go, Spring Boot and Kafka backend with a full ML toolchain (PyTorch, Hugging Face Transformers, vLLM, Kubeflow, MLflow), pointing to in-house model training and LLM serving. Current projects on financial document and photo annotation suggest ongoing investment in labeled training data.
Gini is a Munich-based software company founded in 2011 that develops proprietary AI for pulling structured data out of invoices, receipts and other financial documents in real time. Its flagship use case lets bank customers pay a bill by photographing it, and a second product links private health insurer apps with banking apps so claims can be submitted and paid in one flow. Customers are banks and insurance companies, primarily in Germany. The company has 11-50 employees and currently recruits only in Germany, with open positions spanning design, engineering and data.
Gini runs Java, Go and Spring Boot services on Kubernetes and Docker, with PostgreSQL, Cassandra, Elasticsearch, Kafka and RabbitMQ, plus PyTorch, Hugging Face Transformers, vLLM, Kubeflow and MLflow for ML.
Job posts point to automating data operations, optimizing query performance, strengthening high availability, and annotating financial documents and document photos for AI training.
Gini is headquartered in Munich, Bavaria, Germany, and currently hires only in Germany across design, engineering and data roles, mostly at senior level.
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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.
