PRACTICAL AI FIELD GUIDES
Guides for building useful, reliable AI experiences
Explore practical articles on AI agents, RAG, integrations, security, and operations. Browse by topic or search for the question you need answered.
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AI Agents
Design useful agents, choose the right level of autonomy, and plan safe human handoffs.
RAG & Data
Make business knowledge searchable with sound retrieval, evaluation, and data practices.
Integrations
Connect assistants to websites, APIs, CRMs, and the tools your team already uses.
Security & Privacy
Set trust boundaries, protect customer data, and design safer AI workflows.
Industry & Applications
See how AI assistants fit real customer and operational workflows.
Evaluation & Operations
Measure quality, monitor production behaviour, and keep improving over time.
Latest articles
Explore new ideas and practical guidance from the ChatNexus library.
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Contextual RAG: Conversation Context, Memory & Retrieval
Contextual retrieval is what lets a RAG assistant understand a follow-up such as “Does that apply to the diesel model too?” without treating it as a brand-new question.… Read guide
7 min read -
Real-Time RAG: Handling Live Data in Retrieval-Augmented Systems
In fast-paced industries—finance, e‑commerce, news, and IoT monitoring—stale information can lead to bad decisions, missed opportunities, or customer frustration. Real‑Time Retrieval‑Augmented Generation (RAG) addresses this challenge by combining… Read guide
7 min read -
Embedding APIs: Integrating Text Similarity into Your Chatbot
In an era when users expect chatbots to understand nuance and context, simple keyword matching falls short. Embedding APIs, which map text to high-dimensional vectors, unlock advanced capabilities—semantic… Read guide
6 min read -
Conversational Agents: Managing Complex Multi-Turn Interactions
In today’s fast-paced world, users expect chatbots to engage in seamless, context-rich conversations that mimic human dialogue. Yet maintaining coherence across lengthy, multi-topic sessions poses significant challenges. Without… Read guide
7 min read -
LLM API Gateway Design: Routing, Security & Reliability
When should you add an LLM gateway? Learn how to handle model routing, identity, usage limits, cache isolation, observability, prompt injection, and provider failure—without assuming a proxy makes… Read guide
7 min read -
Hybrid Cloud LLM Deployment: Data Flows, Latency & Trade-offs
A practical guide to hybrid LLM deployment: map prompts, logs and fallbacks; enforce placement policy; measure latency; and test privacy, cost and recovery assumptions. Read guide
5 min read -
Cost Optimization for LLM Hosting: Maximizing ROI
Understanding the Cost Structure of LLM Hosting LLM hosting costs break down into several components. Compute is the largest: GPU or CPU cycles consumed during inference and (if… Read guide
7 min read -
Open Source vs Proprietary LLMs: Building Cost-Effective Chatbots
The choice between open-source and proprietary language models is not a simple cost comparison. It affects data handling, deployment, model control, operational effort, performance, support, and the ability… Read guide
2 min read -
Augmented Reality Overlays: RAG Information in AR Environments
Augmented Reality (AR) overlays enrich users’ perception of the physical world by superimposing digital content—text, images, and 3D models—onto real objects. When combined with Retrieval-Augmented Generation (RAG) systems,… Read guide
6 min read -
RAG in Mobile Apps: Native, Cloud and Hybrid Integration
Compare server-side, on-device and hybrid RAG for mobile apps. Choose by data access, freshness, offline needs, battery, storage and security—not untested speed or SDK promises. Read guide
6 min read -
AI for Discord Communities: Support, Privacy & Moderation
A practical guide to Discord community support bots: use explicit commands, request minimal permissions, ground answers in approved sources, protect member data, and keep consequential moderation decisions human-reviewed. Read guide
6 min read -
Conversation Analytics: Turn Chat Data into Better Decisions
A practical guide to reading chatbot conversation patterns: define trustworthy metrics, review model labels carefully, protect transcript data, and turn evidence into measured service improvements. Read guide
6 min read