Enterprise AI Orchestration
RAG AI Agent Development Services
Unlock enterprise knowledge with RAG-powered agents. We build secure, factual, and verifiable AI systems that ground LLM reasoning in your proprietary data.
What is Retrieval-Augmented Generation (RAG)?
RAG combines LLM reasoning with real-time external knowledge retrieval. Instead of relying solely on static training data, agents proactively fetch relevant documents to provide accurate, context-aware answers with verifiable sources.
Retrieval
Fetch relevant documents from your private knowledge base instantly.
Augmentation
Inject found documents into the agent’s reasoning window.
Generation
Synthesize factual answers using retrieved context.
Verification
Every response comes with clickable source citations.
Standard Model
Traditional LLM Agent
- Fixed training knowledge cutoff
- High risk of hallucination (faking facts)
- Limited context about your private data
- No source verification links
Custom Swarm
RAG AI Agent
- Real-time knowledge synchronization
- 100% accuracy on proprietary documents
- Full traceability with citation trails
- Secure, private data processing
Knowledge Base Setup & Architecture
1
Ingestion
PDFs, SQL, APIs
2
Preprocessing
Cleaning & Chunking
3
Embedding
Vectorization
4
Storage
Vector DB Indexing
5
Retrieval
Semantic Search
Vector Database Selection Guide
Pinecone
Managed, Serverless, Enterprise-Ready.
Weaviate
Open-source, Hybrid Search, Multi-modal.
Milvus
High-performance, Cloud-Native, Fast.
Qdrant
Filtering, Fast Search, Rust-based.
pgvector
PostgreSQL Native, Easy Integration.
RAG AI Agent Industry Use Cases
Customer Support
Answering complex product queries using full company knowledge bases.
Legal Research
Searching thousands of contracts and regulatory filings for precise clause retrieval.
Healthcare
Providing medical professionals with instant access to clinical guidelines and patient history.
Finance
Automating market research and regulatory compliance checks across diverse reports.
RAG AI Agent Development Pricing
Basic RAG Agent
$25K - $60K
- Small knowledge base (<100 docs)
- Single Vector DB
- Basic Semantic Search
Advanced RAG System
$25K - $60K
- Up to 5K documents
- Hybrid Search + Reranking
- Real-time Indexing
Enterprise Platform
$60K - $150K+
- Million+ document scale
- Multi-Vector DB support
- Fine-tuned embedding models
Build a Knowledge-Powered AI Agent
M TECHUB LLC helps you design, deploy, and optimize RAG systems for enterprise-grade accuracy and reliability.
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