How long does it take to set up a RAG API

TL;DR: Under 5 minutes from signup to your first search result. Ragex requires five steps: create an account, get an API key, create a knowledge base, upload a document, and call the search endpoint. No databases to provision, no models to configure, no infrastructure to deploy.

What does the setup process look like?

The entire setup fits in a single terminal session:

1. Sign up — create an account and receive your API key (30 seconds)
2. Create a knowledge base — one API call with a name (1 second)
3. Upload a document — send a file or raw text (1 second for the request, then async processing)
4. Wait for processing — the document moves through parsing, chunking, and embedding (seconds for small files, 1-2 minutes for large PDFs)
5. Search — call the search endpoint with a natural language query (milliseconds)

The bottleneck is document processing time, which depends on file size and type. A 5-page PDF processes in under 10 seconds. A 200-page technical manual might take a minute or two. Once processing completes, search is instant.

How does this compare to building RAG from scratch?

Building a RAG pipeline yourself typically takes two to four weeks of engineering time. The work breaks down roughly like this:

Task	Time
Evaluate and select a vector database	2-3 days
Set up document parsing for your file types	3-5 days
Implement chunking strategy	1-2 days
Integrate an embedding model	1-2 days
Build the search endpoint with reranking	2-3 days
Testing and edge cases	2-3 days
Total	11-18 days

And that estimate does not include ongoing maintenance — model upgrades, database scaling, parser updates, and debugging failed document processing. With Ragex, those tasks disappear entirely. You bring documents and queries; the API handles the rest.

What do I need before starting?

Nothing beyond a programming environment. Ragex provides SDKs for Python (pip install ragex) and TypeScript (npm install ragex). You can also use plain HTTP calls with any language that supports REST APIs.

You do not need to provision servers, choose embedding models, or configure vector dimensions. The API supports 16 file types out of the box — PDF, DOCX, PPTX, XLSX, images (PNG, JPG, WEBP, TIFF), and text formats (TXT, MD, HTML, CSV, TSV, JSON). Upload any supported file and the API parses it automatically.

Can I have a working prototype in one session?

Yes. Here is a complete TypeScript example that goes from zero to search:

import { RagexClient } from 'ragex';

const client = new RagexClient({ apiKey: 'YOUR_API_KEY' });

const kb = await client.createKnowledgeBase({ name: 'Docs' });
const doc = await client.uploadDocument(kb.id, file);

// Wait for processing
let status = doc.status;
while (status !== 'ready' && status !== 'failed') {
  await new Promise(r => setTimeout(r, 2000));
  const updated = await client.getDocument(kb.id, doc.id);
  status = updated.status;
}

const results = await client.search(kb.id, { query: 'setup instructions', top_k: 5 });
console.log(results.results[0].text);

This is production-ready code, not a prototype hack. The same five calls work at scale — add more documents, more knowledge bases, more queries. Reranking is enabled by default for better result quality.

What about scaling after the initial setup?

Scaling requires zero additional configuration. Upload more documents to the same knowledge base and they are automatically indexed and searchable. The API handles storage, indexing, and query load internally.

Plans start at $29/mo (Starter), with Pro at $79/mo and Scale at $199/mo for higher document limits and throughput. You do not need to resize databases or upgrade server tiers — the managed API scales with your usage.

FAQ

Do I need DevOps experience to set up a RAG API?

No. If you can make HTTP requests or use a Python/TypeScript SDK, you can set up Ragex. There is no infrastructure to deploy, no Docker containers to run, no Kubernetes clusters to manage. The entire integration is API calls.

How long does document processing take for large files?

Processing time scales with document size and complexity. A 10-page PDF processes in seconds. A 500-page document with tables and images takes 2-5 minutes. Documents process asynchronously, so you can upload multiple files concurrently without blocking your application.

Can I start on a free tier and upgrade later?

Plans start at $29/mo for the Starter tier. Each tier increases document limits and throughput. You can upgrade at any time without re-uploading documents — your knowledge bases and indexed content carry over to the new plan.

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Last updated: 2026-03-09