#1 Hiring AI Talent
Hiring AI experts or consultants is typically the largest expense. While reskilling employees may save costs, it extends ramp-up time.
Calculate fully-loaded costs for new hires, contractors and training. Note that developing in-house talent can create long-term efficiencies.
#2 Building Infrastructure
Compute, storage and bandwidth costs vary based on factors like:
Carefully evaluate infrastructure costs during planning.
#3 Deploying Software
RAG solutions require various software like data connectors, chatbots, vector search and large language models. Consider open source vs. commercial options, licensing, security and support costs. Buy vs. Build scenarios should be compared.
Answering the Buy vs. Build Dilemma
The costs add up quickly when companies choose to build solutions themselves. Maintenance, support, operational costs and more create a total cost of ownership (TCO) that is typically 2x higher than leveraging SearchBlox’s dedicated solutions
#4 LLMs
Large Language Model (LLM) costs correlate directly to usage and content volume. Estimating chatbot usage and content needs is key for cost predictability.
#5 Production Support
Effective RAG solutions require ongoing data updates and maintenance. Support costs should account for high user volumes and real-time conversations.
#6 Legal & Compliance
Involve legal and compliance teams early to avoid risks. Auditing capabilities may be required.
