Weaviate is an open source vector search engine that stores both objects and vectors, allowing for combining vector search with structured filtering with the fault-tolerance and scalability of a cloud-native database, all accessible through GraphQL, REST, and various language clients.
On the Weaviate Podcast users share how they are using Weaviate in their use cases.
Search for comments using Weaviate's semantic search features with Orchest, Weaviate, and Streamlit.
Jina AI is a cloud-native neural search framework and in this podcast, Han Xiao the CEO of Jina AI is telling about all the interesting elements at stake here.
Karen Beckers, Data Scientist from Squadra Machine Learning Company, gives insightful information about how to use vector search in eCommerce.
Alex Cannan, a Machine Learning engineer at Zencastr, talks with Connor Shorten about a really exciting use case of applying search to look through podcast transcription. Topics discussed are the need for fine-tuning, building your own vector database versus Weaviate, data privacy for Deep Learning applications, and many more!
Katie is a knowledge management bot, continuously improving, self-learning, and trained by humans. Under the hood, Katie is powered by the Weaviate vector search engine, during this podcast, Katie's Michael Wechner will talk about all things vector search and more!
NLP frameworks like Deepset's Haystack are powerful tools to help data scientists and software engineers work with the latest and greatest in natural language processing. In this interview, Malte Pietsch will be talking about Haystack and how they leverage the Weaviate vector search engine as a persistent storage engine for their data and vector representations.
Join Connor Shorten and Charles Pierse (Keenious) for the second Weaviate vector search engine Podcast. During the show, they will be discussing how Keenious uses Weaviate and broader, all things NLP!
There is a growing, global community of Weaviate users. Consider giving us a try by downloading a container and by giving us a Github star if you like what you see.
We offer Weaviate as a fully managed service (including optional ML-inference). Does your use case contain sensitive data or do you want to keep full control over where the data resides? Then we can offer a hands-off managed service on your own cloud infrastructure.
Fully managed Weaviate on the Weaviate Cluster Service
Direct support from our solution engineers
Production ready Service License Agreements (SLA)
Managed or 3rd-party ML-Inference
We offer variable pricing with discounts for larger organizations. Get in touch with us and we’ll figure out something that works for everyone.
Google Cloud Platform
Amazon Web Services
SeMI Technologies is the company behind Weaviate and responsible for the managed services.
If you decide to use Weaviate open-source, you have 100% control and rely on community support. The paid services provide direct support, take all management away, and -often crucial if you are an enterprise- the right SLAs to run a database like Weaviate in production.
Yup! Ask us about it.