The Problem

RAG problems start upstream.

Everything that happens to your documents before retrieval matters. Parsing, layout detection, chunking strategy, metadata extraction, permissions tagging. It all compounds downstream.

Every team building RAG systems eventually discovers this: their retrieval isn't broken, their document processing is. Tables mangled during parsing. Chunks split mid-sentence. Document structure flattened. Metadata stripped before it reaches the vector store.

By the time you're debugging hallucinations, the damage was done upstream. The broken output exists right now, invisible, waiting to surface in production.

We built VectorFlow because most teams don't discover these problems until they're deep in a conversation getting weird responses. See what happens to your documents before you commit.

What We Believe

Product principles.

Visibility over abstraction. If you can't see what's happening, you can't fix it. Transformations should be inspectable.

Configuration should feel like pair programming. VectorFlow recommends. You decide. It configures the tools and runs the transformation. See the results, iterate in place.

Fail fast, iterate faster. Problems should surface at configuration time, not when a user asks a question and gets nonsense back. And fixing them shouldn't mean reprocessing everything.

Team

Meet the creators.

Nicholas Richu

Nicholas Richu

Founder

Data infrastructure and developer tools background. Previously product at Airbyte, Honeycomb, HashiCorp, and IBM. Focused on the problems that emerge when pipelines meet AI.

AirbyteHoneycombHashiCorpIBM

Get Started

Early Access

The core is working. We're partnering with teams to get the edge cases right before opening up more broadly.

Book a Call

Questions? hello@vectorflow.dev