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vectorize

by Vectorize Inc.

System Card

OrganizationVectorize Inc.
Released2023-09
Architecturevector-rag / managed RAG pipeline builder
DetailsVectorize is a managed platform for building end-to-end RAG pipelines with a visual no-code interface. It automates document ingestion, chunking strategy selection, embedding model choice, vector store deployment, and retrieval API generation. Also includes evaluation tooling to measure pipeline quality. Cloudflare offers a product also named Vectorize as part of its Workers AI stack.
Parameters—
Domainrag-retrieval
Open SourceNo
WebsiteVisit
managed-pipelineno-codeingestionchunkingevaluation

Capability Profile

Benchmark Scores

5 of 14 benchmarks
Long-Context Retrieval
2/5
RULER
66.513p
NIAH
no data
LooGLE
no data
LongBench
603p
∞Bench
no data
Multi-Turn Recall
0/2
LoCoMo
no data
MemoryBank
no data
Cross-Session Memory
0/1
LongMemEval
no data
Multi-Hop QA
2/3
BABILong
no data
MultiHop-RAG
59.31p
HotpotQA
62.220p
Agent Task Memory
0/1
AgentBench-Mem
no data
Personalization
0/1
PerLTQA
no data
Factuality / Grounding
1/1
RAGAS
66.633p
Sources:vectorize vendor documentation; evaluated on HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering (Stanford / CMU, 1809)vectorize vendor documentation; evaluated on LongBench: A Bilingual, Multitask Benchmark for Long Context Understanding (Tsinghua KEG, 2308)vectorize vendor documentation; evaluated on MultiHop-RAG: Benchmarking Retrieval-Augmented Generation for Multi-Hop Queries (HKUST, 2401)vectorize vendor documentation; evaluated on RAGAS: Automated Evaluation of Retrieval-Augmented Generation (Exploding Gradients, 2309)vectorize vendor documentation; evaluated on RULER: What's the Real Context Size of Your Long-Context Language Models (NVIDIA, 2404)