The Retrieval Infrastructure for AI

Every AI system needs context. ZeroEntropy fixes broken retrieval with higher relevance, lower latency, and lower token waste.

ZeroEntropy turns noisy retrieval into near-perfect relevance. When your models get better context, they give better answers.

Many teams switch to ZeroEntropy for the unmatched latency of our models and search. Fast enough for real-time AI applications, agents, and user-facing search, even at large scale.

zembed-1 outperforms leading embedding models even at lower dimensionality.

zerank-2 is our state-of-the-art reranker. Get dramatically more accurate retrieval with one line of code.

End-to-end managed retrieval. Embedding, reranking, and query generation in a single API.

zerank-2 is our state-of-the-art reranker. Get dramatically more accurate retrieval with one line of code.

Integrate ZeroEntropy in minutes. Models only, or end-to-end retrieval. Production-ready.

Create an API Key at https://dashboard.zeroentropy.dev

from zeroentropy import ZeroEntropy
zclient = ZeroEntropy()
response = zclient.models.rerank(
model="zerank-2",
query="What is Retrieval Augmented Generation?",
documents=[
"RAG combines retrieval with generation...",
],
)
for doc in response.results:
print(doc)

Deploy in your own cloud with dedicated infrastructure. Available on AWS Marketplace and Azure.