We're building the data layer of RAG.
CHUNKZA AI is a 2026 startup on a mission to make chunking a first-class engineering discipline — because retrieval quality is decided long before the model.
Chunking is the most under-engineered layer of RAG.
The industry poured years into embedding models, vector indexes, and rerankers — and treated splitting as a one-liner. We think that's backwards.
In advanced RAG systems, "garbage in, garbage out" is decided at the chunk. A model can only retrieve what was preserved at the split. Cut a table in half, lose a row. Slice a section mid-thought, lose the argument. Split by character count, and you've built a retrieval system on noise.
CHUNKZA treats chunking as engineering: layout-aware, semantically boundary-aware, parent-child linked, and visualized end to end. We give teams the same control over their data layer that they already have over their model layer.
We're a small, senior team of AI engineers and knowledge-base architects who got tired of debugging retrieval in production. CHUNKZA is the tool we wish we'd had.
At a glance
- Founded
- 2026, Singapore
- Stage
- Seed, backed by AI-native investors
- Team
- Senior AI & data engineers
- Headquarters
- Singapore · remote-friendly
- Customers
- Enterprise KB & copilot teams
Four things we won't compromise on.
The source matters most
Every downstream failure in RAG traces back to the data layer. We obsess over it so you don't have to.
Observable over clever
A pipeline you can inspect beats a black box that's slightly smarter. We make the invisible visible.
Reproducible by default
Every chunking policy is versioned, diffable, and replayable. No more 'why did retrieval change?'
Your data is yours
We never train on customer data. Provenance, privacy, and permission-aware retrieval are non-negotiable.
A short timeline of a young company.
2026
CHUNKZA founded
Started in a Singapore basement with one thesis: chunking is the most under-engineered layer of RAG.
2026 Q2
First private beta
Layout-aware + semantic splitting shipped to a dozen enterprise design partners.
2026 Q3
Diagnostic panel
Live boundary preview, embedding map, and strategy diff — the visibility layer went live.
2026 Q4
Public launch
General availability of the Team plan and retrieval replay across major vector stores.
Build the data layer of RAG with us.
We're hiring senior engineers and talking to design partners every week. Come shape chunking with us.