What a RAG build includes
RAG connects Claude to your documents and data. A production RAG system requires careful design across ingestion, retrieval and quality.
Ingestion
Document parsing and pipeline
Ingest documents from files, databases or APIs. Parse structured and unstructured content, handle format variety and data cleanup.
Retrieval
Chunking and ranking
Design chunking strategies that preserve semantic meaning. Rank retrieved passages by relevance and handle edge cases where documents overlap.
Quality
Evaluation and testing
Build test sets that validate retrieval accuracy. Measure recall, precision and relevance. Benchmark against baselines and production targets.
Production
Hardening and monitoring
Deploy with observability, cost controls and fallback strategies. Monitor retrieval quality drift over time. Plan updates for new documents.
Typical project shapes
RAG projects vary by document type and scale.
- Small homogeneous: Single document type (e.g., PDFs only). 4 to 8 weeks. Team size: 1 architect, 1 builder.
- Medium mixed: Multiple formats and domains. 8 to 12 weeks. Requires retrieval tuning and quality gates. Team: 1 architect, 2 builders.
- Large complex: Diverse sources, custom ingestion, real-time updates. 12 to 16 weeks. Full team with subject-matter expert validation.
Team composition
A RAG project works best with clear role separation.
Architect
System design lead
Certified architect who owns retrieval strategy, chunking decisions and quality targets. Stays involved through production hardening.
Builders
Implementation team
One to two developers who build ingestion pipelines, embeddings and retrieval systems. They execute architect decisions and report on technical constraints.
Your side
Domain expert
Someone from your team who knows the data, validates retrieval quality and spots edge cases the team may miss.
Engagement models
Choose the structure that matches your project.
Design only
Architecture review
Architect conducts a design sprint. Delivers a detailed RAG architecture, chunking strategy and retrieval plan for your team to build.
Full delivery
Build and deploy
Full team builds, tests and deploys a production RAG system. Includes knowledge transfer and runbooks for ongoing maintenance.
Hybrid
Design plus training
Architect designs the system. Certified builders work with your team during implementation for knowledge transfer and quality gates.
Frequently asked questions
What is retrieval-augmented generation?
RAG connects Claude to your documents by retrieving relevant passages and feeding them into the model. RAG lets Claude answer questions about your data without retraining and without hitting context limits.
What is involved in a RAG build?
A RAG build includes document ingestion and parsing, text chunking strategy, embedding and vector storage, retrieval ranking, quality evaluation and production hardening with monitoring and updates.
How long does a RAG project take?
Small RAG projects with homogeneous documents typically run 4 to 8 weeks. Large projects with document variety, retrieval tuning and quality gates typically run 12 to 16 weeks. Scope and complexity drive timeline.
What team do we need?
A RAG project typically needs one certified architect for design and decisions, one to two builders for implementation, and a subject-matter expert from your side for data validation. Team size scales with document variety.
Ready to build RAG
Submit your document scope and retrieval needs. We'll propose a team composition and timeline within five business days.
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