Custom RAG development services

Retrieval-augmented generation is an AI approach that blends LLM features with external knowledge sources. It doesn’t fully rely on trained data only but retrieves up-to-date information from databases and documents to generate more accurate, grounded responses.

In practice, RAG uses your company’s actual records.

Vector databases are systems specifically designed to store and search data based on meaning, not keywords. They convert different types of content (text, images) for straightforward similarity-based search.

This allows AI systems to find the most relevant pieces of information when queries are vague.

RAG helps with hallucinations by grounding AI responses in verified knowledge sources, which means they are:

• Always fact-based rather than purely speculative
• Already aligned with relevant enterprise information
• And traceable

RAG provides greater trust in nuanced business cases.

RAG and LLM fine-tuning are solving different problems, and in many scenarios, they work best together.

• RAG systems are better for accessing up-to-date information without retraining the model
• And fine-tuning is better for teaching specific behaviors/tone/patterns

RAG systems are also typically faster to implement and easier to update.

Project costs will depend on many individual nuances: size, complexity, customization, integrations, and more.

For most enterprise solutions:

• It starts from $30,000-$80,000 for prototypes
• And ranges to $150,000-$500,000+ for larger, production-ready products

Did not really help?

Let’s discuss how much your envisioned RAG solution would cost.

Project timelines will depend on many different things but follow a similar stage-by-stage approach.

In practice, this means:

• MVP systems: 4-8 weeks
• Enterprise solutions: 2-4 months
• More complex (governed, multi-source) RAG platforms: 4-6 months, and longer

Still confused?

Let’s estimate how long a tailored RAG system would take from discovery to rollout.

We have PhD-level experts in mathematics and physics, data scientists, ML specialists, MLOps professionals. Most have prompt engineers.

RAG agents, LLM development, generative AI, multimodal AI, and everything in between – we handle it all.

We provide end-to-end services:

• RAG consulting & strategy
• RAG architecture design
• Knowledge mapping
• Retrieval engineering
• Model grounding
• Context orchestration
• RAG development
• RAG integration
• Governance, guardrails & security
• Monitoring, evaluation & optimization

To get a consultation, just drop a line, and we will get in touch.