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App Corp
Full-service software engineering
Engineering your experience…
App Corp
Full-service software engineering
Engineering your experience…
Is RAG Right for Your Data?
Not every knowledge problem needs RAG. This assessment evaluates your documents, data quality, and use case to determine if RAG is the right approach — and what you need to prepare.
RAG is appropriate when you have: 100+ documents that change over time, questions that require specific factual answers, a need for citations, or domain-specific knowledge not in public LLMs. RAG is NOT appropriate for: small static datasets (use fine-tuning), simple FAQ (use templates), or real-time data (use APIs).
Configure your requirements below to get a personalized estimate.
Document types, volume, and format.
What questions should the system answer?
Get scored on data quality, volume, and format.
Receive a readiness score and improvement plan.
Minimum 100+ documents for RAG to be cost-effective vs alternatives
Clean, structured documents produce better retrieval than messy PDFs
Factual questions work well; opinions and synthesis may need different approaches
RAG excels when knowledge changes; static content may be fine-tuned
1000+ internal documents searchable by employees
Dev Cost
$25K–$60K
Timeline
8–16 weeks
Monthly
$200–$800
500+ pages of product docs for customer self-service
Dev Cost
$20K–$50K
Timeline
6–12 weeks
Monthly
$150–$600
100+ contracts for clause extraction
Dev Cost
$40K–$90K
Timeline
10–20 weeks
Monthly
$300–$1,200
50 frequently asked questions
Dev Cost
$5K–$15K
Timeline
2–4 weeks
Monthly
$50–$200
Your readiness assessment results.
| Cost Item | Range | Notes |
|---|---|---|
| Document quality | 0–25 points | Cleanliness, structure, and format consistency |
| Document volume | 0–25 points | Sufficient volume for RAG to be cost-effective |
| Use case fit | 0–25 points | How well RAG matches your query patterns |
| Technical readiness | 0–25 points | Existing infrastructure and team capabilities |
This assessment provides initial guidance. For a detailed analysis of your knowledge system requirements, talk to an App Corp engineer.