Enterprise RAG Systems & Internal AI Knowledge BasesMFA Faizan
I build secure, Retrieval-Augmented Generation (RAG) systems that turn your company's scattered data into an intelligent, conversational knowledge base.
Rather than relying on generic AI, I connect Large Language Models (LLMs) directly to your private documents, wikis, and databases so your team can instantly query company-specific information with zero hallucination.
The Business Impact
Employees spend up to 20% of their day searching for internal information. This Proof-of-Concept (PoC) deployment eliminates that waste, giving your team instant, accurate, and source-cited answers based strictly on your proprietary data.
What You Get in This PoC Setup:
ā¢ Vector Database Architecture: Securely embedding and storing a subset of your core company data (Pinecone, Qdrant, etc.).
ā¢ Zero Hallucination Guardrails: AI constrained strictly to your private documentation to ensure 100% factual accuracy.
ā¢ Strict Data Privacy: Enterprise-grade security so your proprietary data is never used to train public models.
ā¢ Interactive Chat UI: A localized or secure web-based interface for your team to test queries.
Message me with a brief description of your data sources (PDFs, Notion, SQL), and we will start building your RAG prototype.
Example work
Starting at$1,500
Duration2 weeks
Tags
Python
API Integration
Machine Learning
Systems Architecture
Artificial Intelligence
Data Pipeline
Large Language Models (LLMs)
Service provided by
MFA Faizan Rawalpindi, Pakistan
- 3
- Followers
Enterprise RAG Systems & Internal AI Knowledge BasesMFA Faizan
Starting at$1,500
Duration2 weeks
Tags
Python
API Integration
Machine Learning
Systems Architecture
Artificial Intelligence
Data Pipeline
Large Language Models (LLMs)
I build secure, Retrieval-Augmented Generation (RAG) systems that turn your company's scattered data into an intelligent, conversational knowledge base.
Rather than relying on generic AI, I connect Large Language Models (LLMs) directly to your private documents, wikis, and databases so your team can instantly query company-specific information with zero hallucination.
The Business Impact
Employees spend up to 20% of their day searching for internal information. This Proof-of-Concept (PoC) deployment eliminates that waste, giving your team instant, accurate, and source-cited answers based strictly on your proprietary data.
What You Get in This PoC Setup:
ā¢ Vector Database Architecture: Securely embedding and storing a subset of your core company data (Pinecone, Qdrant, etc.).
ā¢ Zero Hallucination Guardrails: AI constrained strictly to your private documentation to ensure 100% factual accuracy.
ā¢ Strict Data Privacy: Enterprise-grade security so your proprietary data is never used to train public models.
ā¢ Interactive Chat UI: A localized or secure web-based interface for your team to test queries.
Message me with a brief description of your data sources (PDFs, Notion, SQL), and we will start building your RAG prototype.
Example work
$1,500