Citai Blog
Articles about AI, RAG, knowledge management, and support automation.
What is RAG? Retrieval-Augmented Generation Explained
Discover how RAG combines intelligent search with generative AI to deliver accurate answers with verifiable sources.
AI Chatbot vs Traditional Chatbot: Why Sources Matter
Compare rule-based chatbots with RAG assistants that cite sources. Why verifiability is a game changer.
How to Automate FAQs with Artificial Intelligence
Learn how an intelligent FAQ system reduces support tickets and responds instantly without consuming LLM tokens.
Intelligent Knowledge Base: A Guide for Businesses
Learn to build an effective knowledge base: documents, FAQs, health score, and smart routing.
Embeddings and Semantic Search: How Context-Aware AI Works
Understand how embeddings transform text into vectors to find information by meaning, not exact words.
How to Reduce Support Tickets with an AI Assistant
Practical guide to implementing an AI assistant that resolves queries automatically and escalates complex ones.
Semantic Cache: How to Reduce LLM Costs by Up to 70%
Discover how semantic caching detects similar questions and avoids repeated LLM calls, saving tokens and money.
Cross-Encoder Reranking: How to Improve Your Chatbot's Accuracy
Learn how cross-encoder reranking dramatically improves RAG response relevance.
Embeddable Chat Widget: From Zero to Production in 5 Minutes
Install an AI assistant on your website with one line of code. Shadow DOM, SSE streaming, themes, pre-chat forms, and smart escalation.
Automatic Language Detection in AI Assistants
How Citai detects the user's language and responds in their language. Heuristics, multilingual embeddings, and content rules.
AI for E-commerce: Automate Product, Shipping, and Returns Support
Complete use case: how an online store can resolve 90% of queries automatically with AI and cut support costs.
AI for SaaS: Automated Onboarding and Smart Technical Support
How SaaS companies use Citai to reduce churn with AI-guided onboarding, 24/7 technical support, and always-updated documentation.
How Much Does an AI Chatbot Really Cost: Complete Breakdown
Real cost breakdown of an AI chatbot: LLM tokens, embeddings, hosting, and how Citai optimizes each component.
Smart Escalation: When AI Should Hand Off to a Human
How to configure confidence-based, manual, and schedule-based escalation. Webhooks with full context to Slack, email, or Zendesk.
Multi-Tenancy in SaaS: Data Isolation with PostgreSQL
How we implement real multi-tenancy with complete data isolation, hierarchical roles, anti-fraud plan enforcement, and enterprise security.
Contextual Retrieval: What It Is and Why It Improves RAG
How enriching each chunk with document-level context before indexing transforms search quality in RAG systems.
Contextual Retrieval vs Standard RAG: Real Metrics
We compare standard and contextualized search in real scenarios: confidence, reranking, and answer quality.
Anatomy of a Contextualized Chunk: Before and After
Step-by-step analysis of how an LLM transforms raw chunks into semantically rich fragments for search.
How to Choose the Ideal Chunk Size for Your Knowledge Base
Practical guide to configuring chunk_size and chunk_overlap based on document type and use case.
Hybrid Search: How to Balance Semantic and Keyword Search in RAG
Learn to adjust the weight between vector search and BM25 to maximize relevance based on your content type.
Confidence Scoring: How to Interpret and Improve Answer Quality
Understand what each confidence level means and what actions to take to go from amber to green.
FAQ vs RAG: When to Use Each Strategy and How to Combine Them
Guide to deciding when to answer with direct FAQ vs full RAG search, and how to optimize the combined flow.
RAG Playground: how to diagnose and fine-tune your knowledge base
Practical guide to using Citai RAG Playground: pipeline diagnostics, parameter tuning, A/B comparison and batch testing.
How to Prepare Your Documents for AI: Complete Optimization Guide
Learn best practices for preparing PDFs, DOCX, Excel, TXT, and Markdown before uploading to Citai. Maximize answer quality with well-structured documents.
Live Chat: How AI and Human Agents Work Together in Citai
Discover how Citai combines automatic AI responses with human agent escalation for real-time hybrid support.
AI Chatbot Security: 2FA, OAuth, Headers and More
Complete security guide for AI assistants: multi-factor authentication, OAuth, HTTP headers, API key hashing, and rate limiting.
GDPR and Privacy in AI Assistants: A Practical Guide
How to comply with GDPR when deploying AI chatbots: data portability, right to erasure, retention, and auditing.
Smart Routing: Automatic Knowledge Base Selection with Embeddings
How Citai automatically selects the best knowledge base for each question using embedding centroids and cosine similarity.
KB Health Score: Monitor and Improve Your Knowledge Quality
Understand how your knowledge base Health Score is calculated and how to improve each component for better answers.
Audit Logging: Complete Traceability for AI Compliance
How audit logs in Citai enable complete action traceability, regulatory compliance, and forensic analysis.
Auto-Inject: How to Connect Your APIs Directly to the Chat Widget
Learn how to configure tools that run automatically with user data for personalized responses from the very first message.
Visual RAG: when document images speak in responses
How Citai automatically extracts images from PDFs and DOCX, associates them with text chunks, and displays them in chat responses. The evolution from textual RAG to visual RAG.
Email Assistant: reply to customer emails with AI in seconds
New Citai module that generates professional email replies using your knowledge base. Pre-analysis, 4 tones, embedded images and full history.
Email Threads: manage complete conversations with AI context
Organize emails into threads with automatic analysis, smart alerts, in-thread search, and response generation with full conversation context.
Email Templates: consistent replies in seconds
Create reusable templates with dynamic variables, multilingual support, and predefined seed templates to start instantly.
Response Style: customize your AI agent's voice
Configure how your email agent writes: signature, preferred tone, custom instructions, format, and length of generated responses.
Knowledge Graph: visualize your RAG pipeline as a neural map
New visual tool in Citai's Playground that displays RAG pipeline results as an interactive graph of nodes and connections.
How we measure the chatbot is not making things up: Faithfulness Detection with NLI
We verify every LLM answer against the retrieved chunks with an NLI model. The faithfulness score catches hallucinations even when confidence is high.
How you measure your chatbot is not getting worse over time: regression testing for RAG
A per-KB Golden Set + 5 metrics + baseline comparison = know before your customer does whether your change improved or regressed the RAG.