Building RAG Apps Workshop

Build practical ‘chat with your data’ capability - learn how to design Retrieval‑Augmented Generation (RAG) systems that are accurate, secure, and ready to deploy.

Large language models are powerful, but they do not inherently know your organisation’s documents, policies, knowledge base, or line‑of‑business content. When teams try to ‘bolt on’ private data without the right architecture, they often get inconsistent answers, weak citation quality, poor relevance, and avoidable risk - especially around permissions and data exposure. That is why RAG (Retrieval‑Augmented Generation) has become the standard approach for building reliable ‘chat with data’ experiences.

LW IT Solutions delivers the Building RAG Apps Workshop as a hands-on, architecture-led session for technical teams. We cover end-to-end RAG fundamentals - data ingestion, chunking and embedding strategies, vector search and ranking, prompt construction, grounding with citations, evaluation approaches, and security patterns. The workshop is stack-aware: it can be aligned to Microsoft and Azure capabilities (for example Azure OpenAI and Azure AI Search) or other tooling you already use. You leave with an architecture blueprint, a practical build plan, and clear next steps for prototyping and productionisation.

Talk through your requirements and leave with a clear next-step plan.

Book a discovery call

Service Overview

Highlights

Hands-on, architecture-led RAG workshop for technical teams
Coverage of ingestion, vector search, ranking, and prompt grounding
Focus on evaluation, citations, and answer quality
Security-aware patterns for private and sensitive data
Aligned to Microsoft and Azure services where required

Business Benefits

Clear understanding of how to design reliable RAG architectures for real data
Reduced risk of inaccurate answers through grounded retrieval and evaluation patterns
Improved security by applying permission-aware ingestion and retrieval approaches
Faster path from idea to prototype with a defined build plan and architecture
Shared understanding across engineering, data, and security teams

Typical use cases

Internal knowledge assistants over policies, procedures, or documents
Customer or partner support chat over controlled content
Engineering teams moving from RAG experiments to production design
Organisations struggling with hallucinations or weak grounding
Teams needing a shared reference architecture for multiple RAG projects

Objectives & deliverables

What Success Looks Like

Understand when and how to use RAG for chat with private data
Design a RAG architecture that fits your data and risk constraints
Define evaluation criteria to measure answer quality and relevance
Identify security and access control requirements early
Produce a clear plan for moving from prototype to production

What You Get

Workshop outputs pack: architecture diagram(s), decisions, and recommended patterns
Implementation checklist: ingestion, retrieval, grounding, evaluation, and operational controls
Risk and constraint log: data boundaries, security constraints, and governance requirements
Prototype/MVP plan with phased next steps
Optional: sample skeleton repository structure guidance (high-level) for your build approach

How It Works

Pre‑work - confirm your data sources, identity model, target use cases, and constraints.
Workshop - teach core RAG concepts and map them to your environment; design the reference architecture.
Synthesis - produce an architecture and backlog with clear next steps for prototyping and rollout.
Playback - validate the plan with stakeholders (engineering, data, and security).

Engagement Options

Virtual Workshop - Remote delivery with shared labs and design sessions
In-Person Workshop - On-site delivery with whiteboarding and hands-on discussion
Workshop Plus - Workshop followed by supported prototype build

Common Bundles

Customers who use this service often bundle with these services

AI & Automation Workshops
Structured AI and automation workshops to identify, validate, and prioritise use cases, producing a delivery-ready backlog with clear constraints.

Data Strategy & Architecture
Define a clear data strategy and target architecture that aligns platforms, governance, security and cost with measurable business outcomes.

Information Protection & Sensitivity Labels
Design and deploy Microsoft Purview sensitivity labels to classify data, apply protection controls, and support safer collaboration across Microsoft 365.