Raptor Data - Version Control for RAG
Git-like versioning for RAG embedding pipelines w/ DX Focus
# Code AssistantWhat is Raptor Data - Version Control for RAG?
Raptor Data is the Stripe for RAG ingestion. A lightweight, fully-typed TypeScript SDK that brings Git-like version control to your embeddings. We handle the messy infrastructure: structure-aware parsing, recursive chunking, and semantic diffing. Instead of re-embedding entire files on every edit, Raptor tells you exactly which chunks changed. Runs anywhere (Node, Edge, Browser). Save 90% on vector costs with one line of code.
Problem
Users manage RAG embedding pipelines without version control, leading to high vector costs and inefficient re-embedding of entire files on every edit.
Solution
A TypeScript SDK that introduces Git-like versioning for RAG pipelines, enabling semantic diffing to identify changed chunks and reducing vector costs by 90% with one line of code.
Customers
Developers and data engineers building RAG applications, particularly those focused on optimizing AI/ML workflows and infrastructure costs.
Unique Features
Semantic diffing for precise chunk updates, structure-aware parsing, edge/browser compatibility, and cost-optimized incremental embedding updates.
Traction
Positioned as "Stripe for RAG ingestion", emphasizes developer experience (DX) and claims 90% cost reduction. Specific traction metrics not publicly disclosed.
Market Size
The global MLOps market is projected to reach $6.9 billion by 2030 (Grand View Research), with RAG adoption accelerating in AI infrastructure.
