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RAG Development
Search and answer across your own documents with retrieval-augmented generation.
What This Service Delivers
Your company already holds its best answers in documents, wikis, tickets, and databases. RAG connects LLMs to that knowledge so employees and customers get grounded, sourced, up-to-date answers — dramatically reducing hallucinations and making your data usable.
View this service as...
Investment
$15,000 – $60,000
Timeline
4–12 weeks
Expected outcome
Grounded responses with citations back to source documents.
Key risks to plan for
Document cleanup services · Fine-tuning of the foundation model · Ongoing content curation
Answer from your data
Grounded responses with citations back to source documents.
Always current
Update your knowledge base and the answers update — no retraining.
Access controlled
Permission-aware retrieval so users only see what they are allowed to see.
Measure quality
Retrieval and answer quality evaluated continuously with real queries.
Investment & Timeline
Starting from
$15,000
Typical project range
$15,000 – $60,000
Typical timeline
4–12 weeks
What's included
- ✓ Ingestion pipeline
- ✓ Vector store setup
- ✓ Search + generation API
- ✓ Evaluation harness
What's not included
- ✕ Document cleanup services
- ✕ Fine-tuning of the foundation model
- ✕ Ongoing content curation
Factors affecting price
Document volume and formatsNumber of access-control systemsAnswer quality requirements
What You Get
Content ingestion and chunking pipeline
Embedding and vector storage
Hybrid search (semantic + keyword)
Permission-aware retrieval
Answer generation with citations
Evaluation and monitoring
Technology
PythonTypeScriptLangChainOpenAI / AnthropicVector DBsFastAPI
Industries
Frequently Asked Questions
RAG vs fine-tuning — which should I use?
RAG is the right default for knowledge questions: it is cheaper, updatable, and auditable. Fine-tuning helps with style and domain behavior. We explain the trade-off on our RAG vs fine-tuning comparison.
Which document types can you ingest?
PDFs, Word, Excel, HTML, Notion/Confluence exports, SQL, and API-sourced content — plus scanned documents with OCR.
Can we control who sees what?
Yes. We build permission-aware retrieval so answers respect your existing access control.
Logical Next Steps
Your Service Lifecycle
Related Resources
Related Insights
Ready to get started with rag?
$15,000 – $60,000 typical range · 4–12 weeks typical timeline. Book a call and we'll scope the highest-value version of this work.