New state-of-the-art production-ready models:

Vectorize your data to gear up your AI stack

Voyage AI builds embedding models, customized for your domain and company, for better retrieval quality.

Revolutionizing AI applications

Our mission is to redefine AI applications by providing a fundamental building block that empowers chatbots and AI systems with unparalleled precision, efficiency, and intelligence.
Where are our data centers located?
OneSingal`s data center are located in European Union, specifically in the Netherlands. These data centers are managed by Google Cloud
Playform (GCP)



https://onesignal.com/blog/how-onesignal-meets-gdpr-compliance-measures
Another question for the proucts?
Correct answer generated by Voyagemap using better model in vectoriazation

Upgrade your retrieval-augmented generation (RAG) stack with Voyage embeddings

High-quality contexts

Enhancing RAG by retrieving more relevant docs.

Less hallucination

LLMs do not hallucinate with accurate contexts.

Modularity

Plug-and-play with any vectorDB and LLM.

Multi-purpose

State-of-the-art quality across domains.

Industry customizable

Engineering, finance, legal, healthcare, etc. 

Company customizable

Ingesting proprietary data and knowledge.

Novel training methods leads to state-of-the-art retrieval accuracy

Algorithm and architecture

New self-supervised loss functions and modern architectures at an unprecedented scale.

Systematic and large-scale data processing

Diverse training data from business domains, tailored to RAG and search.

Unlabeled finetuning

Advanced finetuning techniques without human labels.

Excited about Voyage embeddings?

Python
Code Embed with Color # Sample code to get embeddings using Voyage AI API
import voyageai

voyageai.api_key = "YOUR_API_KEY"

text = "Vectorize your data to gear up your AI stack."
embedding = voyageai.get_embedding(text, model="voyage-01")

print(embedding)
Python
Code Embed with Color # Sample code to get embeddings using Voyage AI API
import voyageai

vo = voyageai.Client(api_key="YOUR_API_KEY")

text = ["Vectorize your data to gear up your AI stack."]
result = vo.embed(text, model="voyage-code-2")

print(result.embeddings)

Contact us for fine-tuned models

Fill out the form to send us a message or directly email Tengyu Ma (CEO) at tma@voyageai.com.

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