30+
Agentic AI implementations
Across Finance, Healthcare, Real Estate, Manufacturing and Print on Demand.
Free ebook · 2026 edition
The complete guide · Updated for 2026
The Complete RAG & Information Retrieval Guide for 2026
A reliable source of knowledge for decision makers, engineers and product managers on Retrieval Augmented Generation and its applications in Agentic AI.
- Build production RAG systems that do not confuse similar products, services or documents.
- Solve the accuracy vs. speed trade-off with patterns proven on 30+ live deployments.
- Pick the right model size and know when smaller models actually outperform bigger ones.
Why this guide
Your trusted source of ground truth
Stay informed on RAG applications in Agentic AI in business workflows to pick your solutions wisely, gain reliable knowledge on what is possible with modern AI systems, and make informed decisions on your development plan.
Prepared by experts delivering RAG-enhanced agentic AI to Finance, Healthcare, Real Estate, Manufacturing and Print on Demand — real implementations that deliver results, summarised in one place.
100%
Engineer-authored
Every chapter is written by people who ship RAG systems to production.
5
Vertical lenses
Finance, healthcare, real estate, manufacturing, print-on-demand — each with concrete examples.
Table of contents
RAG Explained: From Concept to Production
Seven decision-ready chapters — written for people who buy, scope, and ship RAG systems. No fluff, no toy demos.
Foundations & vector retrieval
How retrieval actually works in production systems.
Disambiguation patterns
Stop confusing similar products, services, and documents.
Accuracy vs. speed trade-offs
Patterns that hold up under real workload pressure.
Model selection & cost
When bigger models lose — and smaller ones win.
Evaluation & metrics
What to measure so you know the system is working.
RAG-readiness audit
Is your stack ready — and what to fix if it is not.
Production case studies
Concrete examples from live deployments.
What is inside
From this ebook you will learn
Practical chapters — no fluff, no toy demos, no hello-world tutorials.
01
How to make sure your systems never confuse similar products or services
02
How to solve the accuracy vs. speed trade-off in real workloads
03
What the true costs of bigger models are — and when smaller ones win
04
How to evaluate your solution and set the right metrics to monitor performance
05
If your systems are RAG-ready — and if not, how to make them so
