I will engineer a production ready rag system and custom ai knowledge base

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abhinavrawat786
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abhinavrawat786
Abhinav

About this gig

Most AI knowledge bases break down in production. They hallucinate answers, fail on complex tables, or lack data security. If your team needs an accurate, reliable RAG system and AI knowledge base, you need production-grade engineering.

As an AI engineer, I build secure, high-performance retrieval architectures that connect your proprietary data to state-of-the-art LLMs.

What I Will Build: Advanced PDF & Table Extraction: Accurate parsing for dense internal documents. Hybrid Search Retrieval: Dense vectors + BM25 keyword search for exact matches. Precision Reranking: Filters noise so models receive only top-tier context. Anti-Hallucination Guardrails: Strict source citations mapped to page numbers. FastAPI & Docker Backend: Clean, asynchronous code ready for production.

My Engineering Process:

  1. Scope document formats and schema requirements.
  2. Configure parsing, vector indexing, and chunking strategies.
  3. Integrate hybrid search, rerankers, and citation validation.
  4. Run validation queries and deliver containerized code.
  • Stop wasting time on fragile templates. Let's engineer your enterprise-grade knowledge engine today. Order now or message me to discuss your custom architecture!

Get to know Abhinav

Abhinav

Full Stack Developer AI SaaS Expert Rapid MVP Builder

  • FromIndia
  • Member sinceSep 2024
  • Avg. response time11 hours
  • Languages

    English
4+ years building AI products and SaaS platforms that users love. I specialize in: → Rapid MVP development (from idea to deployed in 7 days) → AI integrations (OpenAI, Anthropic, Hugging Face, custom models) → Full-stack SaaS architecture (React, Node, Python, Supabase) → Helping founders validate & raise capital Tech Stack: JavaScript/TypeScript, React, Next.js, Python, Node.js, Supabase, Stripe, Docker, OpenAI/Claude APIs Experience: Early-stage founders, VC-backed startups, agencies, SMBs Portfolio: 150K+ users across 20+ products, $2M+ in funding supported