AI & Modern Stack
Your RAG pipeline is only as clean as your ingest step.
CSVbox handles the messy user-facing part of document ingest: multi-format uploads, schema enforcement, and clean structured output — before anything hits your embeddings.
- 15 min to live
- SOC 2 + GDPR
- Private Mode available
- Your RAG system returns irrelevant chunks because ingest includes headers, footers, and OCR noise.
- Users upload Excel, PDF, CSV, and screenshots. Your pipeline handles one of those well.
- You're rebuilding the file-validation layer on top of LlamaIndex or LangChain.
How CSVbox solves it
A clean handoff to your vector pipeline
Multi-format in one widget
PDF, Excel, CSV, image, doc — all handled by the same UX.
Schema-on-ingest
Define fields → your embedding pipeline gets predictable shape.
Pre-vectorization transforms
Strip boilerplate, normalize units, resolve dates before embeddings run.
Webhook to your pipeline
Pinecone, Weaviate, pgvector, or your own API — CSVbox just hands off clean rows.
CSVbox let us offer a self-serve CSV import experience for our users without having to build and maintain the entire system ourselves.
Security & compliance included
- SOC 2 Type II
- GDPR
- AES-256
- TLS 1.3
- US / EU residency
- Private Mode
- No AI training
Chain into your RAG ingest
JavaScript
window.csvbox.onData(async (rows) => {
await fetch('/api/rag/ingest', {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({ rows }),
})
})vs DIY preprocessing
| Raw → LangChain | DIY preprocessing | CSVbox | |
|---|---|---|---|
| User-facing UI | DIY | DIY | Drop-in widget |
| Multi-format | Partial | Partial | Full |
| Schema enforcement | No | DIY | Built-in |
| Private Mode | N/A | DIY | Yes |
Frequently asked questions
Does CSVbox do the embeddings?
No — we hand off clean structured data; you embed.
Can I chain into LangChain or LlamaIndex?
Yes — webhook into your existing pipeline.
PII handling?
Private Mode keeps data client-side; use transforms to redact before export.
Is there a doc cap?
Usage-based by rows; see pricing.