RAG Development & Consulting Services

Retrieval-Augmented Generation (RAG) is an AI approach that connects a large language model to your business knowledge. When a user asks a question, the system retrieves relevant information from approved sources—such as documents, databases, knowledge bases, or APIs—and uses that information to generate a grounded answer. RAG can also show citations, helping users verify where an answer came from.

Agentic RAG extends standard retrieval by letting the AI plan multi-step actions breaking a request into sub-questions, querying multiple sources, and validating findings before responding, instead of doing a single retrieval-then-answer pass.

Graph RAG retrieves based on relationships between entities people, products, transactions rather than just text similarity. It’s useful when an answer depends on how things connect, not just what’s written.

RAG and fine-tuning solve different problems. RAG retrieves current information from your documents and data at the time of a query, making it suitable for knowledge that changes often and for answers that need citations. Fine-tuning adjusts a model’s behavior, tone, format, or task performance using training examples. Many enterprise AI solutions use both: RAG for current, verifiable knowledge and fine-tuning for consistent behavior or specialized outputs.

RAG improves response accuracy, reduces hallucinations, and enables real-time access to enterprise data, making AI systems more reliable and context-aware.

A focused RAG proof of concept or pilot can typically be built in 4–6 weeks when the data sources and use case are clearly defined. Enterprise RAG implementations can take longer because they may require data preparation, integrations, access controls, security reviews, evaluation testing, and phased rollout. The final timeline depends on data volume, document quality, number of integrations, and deployment requirements.

Costs range from $15,000–$30,000 for a basic RAG chatbot, $40,000–$80,000 for a production multi-source system, and $80,000–$150,000+ for a full enterprise deployment — plus $500–$5,000/month in ongoing infrastructure once live.

Yes, RAG systems can be integrated with CRMs, ERPs, SaaS platforms, and internal tools through APIs, enabling seamless workflows and data access.