Overview
Engineered a lightweight, no-code RAG solution to bridge the gap between static cloud storage and interactive AI. The system monitors Google Drive directories, automatically ingesting newly uploaded documents of various formats into a vector database to enable natural language querying.
Achievements
Rapid Internal Adoption: Successfully deployed a functional knowledge management tool within one week, immediately streamlining internal documentation workflows. Eliminated Manual Indexing: Automated the entire document lifecycle, reducing the time from "file upload" to "queryable insight" to under 60 seconds.
Responsibilities
- Developed automated ETL workflows in n8n to synchronize cloud storage with Pinecone vector embeddings.
- Configured semantic search parameters to optimize retrieval accuracy for technical and legal documentation.
- Implemented a natural language interface allowing non-technical users to extract complex data from PDFs and spreadsheets.
This project was delivered by
Oleksandr N.
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