Retrieval (RAG)16 companies

16 companies, 16 swept. The median identity score is 83 of 100. Rows are ordered by readiness; rows not yet rated sit last.

16 companies · 16 swept · last sweep 2026-09-16

Identity scores in Retrieval (RAG)swept15 swept

83/100

median

median 83

0identity score, 0-100100

15 swept

Ranked by readiness

#1
Cohere
cohere.com
Provides generative language models and retrieval optimization for enterprise AI applications.
Retrieval (RAG)
bots partly✓ llms.txt
92/100
#1 of 16 in Retrieval (RAG)
#2
Unstructured
unstructured.io
Converts unstructured documents into clean structured data for AI applications.
Retrieval (RAG)
bots in— llms.txt
87/100
#2 of 16 in Retrieval (RAG)
#3
LangChain
langchain.com
Builds and deploys agents with observability, evaluation, and monitoring tools.
Retrieval (RAG)
bots in— llms.txt
81/100
#3 of 16 in Retrieval (RAG)
#4
Pinecone
pinecone.io
Stores and retrieves vector embeddings at scale for retrieval-augmented generation and agent knowledge systems.
Retrieval (RAG)
bots partly✓ llms.txt
76/100
#4 of 16 in Retrieval (RAG)
#5
Qdrant
qdrant.tech
Stores and searches vectors at scale with metadata filtering, hybrid search, and reranking.
Retrieval (RAG)
bots in✓ llms.txt
76/100
#5 of 16 in Retrieval (RAG)
#6
Jina AI
jina.ai
Converts URLs to markdown and provides multimodal embeddings and reranking for search and retrieval systems.
Retrieval (RAG)
bots in— llms.txt
74/100
#6 of 16 in Retrieval (RAG)
#7
Reducto
reducto.ai
Parses documents into structured data with layout preservation, table extraction, and bounding box citations.
Retrieval (RAG)
bots in✓ llms.txt
74/100
#7 of 16 in Retrieval (RAG)
#8
LlamaIndex
llamaindex.ai
Parses and extracts structured data from complex documents using agentic OCR and layout-aware processing.
Retrieval (RAG)
bots in— llms.txt
70/100
#8 of 16 in Retrieval (RAG)
#9
Zilliz
zilliz.com
Manages vector data for AI applications with real-time search, discovery, and analytics on a single platform.
Retrieval (RAG)
bots partly✓ llms.txt
70/100
#9 of 16 in Retrieval (RAG)
#10
Chiri
chiri.ai
Embeds engineering teams to build production AI applications and agents integrated with your existing software and data.
Retrieval (RAG)
bots in✓ llms.txt
67/100
#10 of 16 in Retrieval (RAG)
#11
turbopuffer
turbopuffer.com
Vector and full-text search database built on object storage, scaling to 256TB per index with sub-10ms latency.
Retrieval (RAG)
bots in✓ llms.txt
63/100
#11 of 16 in Retrieval (RAG)
#12
Weaviate
weaviate.io
Vector database that stores, indexes, and searches high-dimensional vectors for retrieval-augmented generation and semantic search.
Retrieval (RAG)
bots partly✓ llms.txt
63/100
#12 of 16 in Retrieval (RAG)
#13
Vectara
vectara.com
Builds retrieval-augmented generation agents with policy enforcement and hallucination detection across on-premises, VPC, and SaaS deployments.
Retrieval (RAG)
bots partly— llms.txt
59/100
#13 of 16 in Retrieval (RAG)
#14
Voyage AI
voyageai.com
Generates embeddings and reranks search results to improve retrieval quality for unstructured data.
Retrieval (RAG)
bots in— llms.txt
49/100
#14 of 16 in Retrieval (RAG)
#15
Chroma
chroma.com
Manufactures optical filters and beamsplitters for imaging, spectroscopy, and scientific applications.
Retrieval (RAG)
bots partly— llms.txt
40/100
#15 of 16 in Retrieval (RAG)
#16
LlamaParse
llamaparse.com
No line written yet.
Retrieval (RAG)
bots in— llms.txt
36/100
#16 of 16 in Retrieval (RAG)

How to read a row

swept: Read by a crawler: HTTP and parsing, no model call. Every row, every week.
measured: The full analyzer run, asked of four engines. Shown only where the company agreed to show it.

Can a retrieval engine find, resolve and quote this site? Four parts, each read by the sweep, each shown beside the total.

Entity 25 · Machine-readable 35 · Retrieval access 20 · Footprint 20

A part that was never read is left out and the total is rescaled to what was. It is never counted as zero.

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