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No-Code Knowledge Ingestion & Semantic Search

AI Engineer2025Oleksandr N.
Oleksandr N.
Oleksandr N.

LLM Engineer / GenAI Engineer

LLM & AI Agents

Key Expertise

Enterprise RAG PlatformsAgentic OrchestrationAI InfrastructureMulti-modal AI Systems

Experience

15+ years

Timezone

GMT +2

Skills

AI / ML

LlamaLangGraphLightLLMGeminiLlama GuardrailsOpenAILangChain

Languages

PythonNode.js

Databases

PineconeElasticsearchPostgreSQLMinIO

Infrastructure

RDSAWSSNSLambdaKubernetesSQSELKDockerEC2

Frameworks

FastAPIn8nApache Airflow

Integrations & Protocols

Google Drive APIOAuth 2.0
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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.

Technologies Used

n8nOpenAIPineconeGoogle Drive API
Oleksandr N.

This project was delivered by

Oleksandr N.

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