Back

vector db

Universal Data Ingestion Pipeline for GenAI & RAG

We built a universal data ingestion and knowledge pipeline that can take almost any type of file – PDF, Excel, XML, JSON, images, audio,…

Universal Data Ingestion Pipeline for GenAI & RAG

We built a universal data ingestion and knowledge pipeline that can take almost any type of file – PDF, Excel, XML, JSON, images, audio,…

  • Strategy

    Standardised ingestion layer for all file types, schema-agnostic knowledge model, multi-backend storage strategy (SQL, vector, graph), optimisation for RAG and agent retrieval patterns, and built-in observability for quality and governance.

  • Design

    Modular processors for PDFs, spreadsheets, XML/JSON and multimedia (OCR and speech-to-text), enrichment services for embeddings, summarisation and entity extraction, pluggable storage adapters for relational, vector and graph databases, and orchestration that exposes the final knowledge layer to GenAI agents, chatbots and analytics tools.

  • Client

    Media company from Germany (EU)

  • Tags

    data ingestion, data lake, data processing, graph db, RAG, vector db

View Project