I will build document search or a rag API with source references

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hglr123
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hglr123
Nik Nastev

About this gig

Make a small set of business documents searchable, with references back to the source.


I build a single-user, single-corpus document retrieval service using Python and Postgres/pgvector or your existing compatible Supabase. Basic delivers document search. Standard and Premium add a question-answering API using one agreed model provider, source references and a fallback when evidence is insufficient.


You receive source code, ingestion instructions, tests and a handover guide. PDF inputs must contain selectable text; TXT and Markdown are also supported. No scans, OCR, spreadsheet parsing or website crawling.


The offer covers a bounded retrieval system, not a general chatbot, long-term conversation memory or model training. A chat UI, enterprise permissions and ongoing hosting are separate. Answers can still be wrong; citations and sample checks help review them. Client-funded infrastructure, embeddings and model usage are required where used.

Get to know Nik Nastev

Nik Nastev

AI Agent Orchestrator, MCP, RAG and Automation

  • FromBulgaria
  • Member sinceOct 2026
  • Languages

    English, Bulgarian, Russian
I'm Nik Nastev, founder of ArtminAI. I design AI agent workflows and build integrations using TypeScript/Node.js, REST APIs, MCP and RAG. My work includes AI-native CMS, persistent vector memory and multi-agent development with separate coding, QA and deployment lanes. I use AI-assisted development with architecture, code review and verification gates. Available for scoped remote projects, integrations and workflow reviews.

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