To keep your internal AI knowledge base current, establish a streamlined update process that integrates policy change notifications, automated content versioning, and regular AI retraining. This ensures your AI assistant delivers accurate, compliant answers as company policies evolve. In practice, […]
You can make legacy engineering drawings and specifications searchable by digitizing them with OCR, indexing them into an AI knowledge base, and using a retrieval-based AI system that allows engineers to search and ask questions in natural language. This turns […]
Training an AI model involves teaching it patterns from large datasets to generate responses, while grounding with Retrieval-Augmented Generation (RAG) uses external knowledge sources at query time to provide accurate, context-specific answers without retraining the model. What does “training” an […]
Employees need training on AI capabilities, limitations, proper usage protocols, data privacy, and troubleshooting to effectively adopt internal AI assistants. Well-structured onboarding ensures user confidence, accurate interactions, and maximizes AI benefits. What happens without proper training? Misuse or overreliance on […]
You can automate FAQ responses with AI by training a knowledge-based AI system on your existing FAQs, help articles, and policies, then deploying it as a chatbot or help widget. This allows customers to receive instant, accurate answers without human […]
You build a cross-department AI assistant by training it on verified knowledge from each team, enforcing role-based access controls, and connecting it to shared workflows. The most effective systems use one AI layer with multiple data sources, ensuring accurate answers […]
To measure the success of an AI customer support implementation, track metrics across efficiency, quality, customer experience, and business impact. Key indicators include ticket deflection rate, first response time, resolution rate, CSAT, escalation rate, and cost per ticket. Together, these […]
Designing knowledge architecture for RAG-based AI involves organizing, structuring, and tagging your data to enable efficient retrieval and accurate AI-generated answers, ensuring your content is clean, relevant, and up-to-date. What is knowledge architecture in the context of RAG? Knowledge architecture […]
Multi-tenant RAG platforms enable organizations to run multiple AI assistants on shared infrastructure while keeping data, configurations, and access separate and secure for each tenant or department. What is a multi-tenant RAG platform? Multi-tenancy allows multiple independent users or groups […]
The most cost-effective AI platforms for non-profits and educational institutions offer flexible pricing, easy deployment, and features tailored for limited budgets. Platforms like CustomGPT provide no-code AI tools, special discounts, and scalable solutions that maximize impact while minimizing costs. Why […]
