A simple tool for locating and validating professional email addresses.
The Pinecone vector database makes it easy to build high-performance vector search applications. Developer-friendly, fully managed, and easily scalable without infrastructure hassles.
Pinecone IntegrationsEasily set up hunter Pinecone Integration without coding. Start automating your workflows and Integrate hunter with Pinecone today.
Triggers when a new campaign is available to your account.
Triggers when a new lead is created.
Trigger when a new collection is create.
This operation returns a list of your Pinecone indexes.
Creates a new lead.
Adds a recipient to one of your ongoing campaigns.
This operation creates a Pinecone collection.
This operation creates a Pinecone index. You can use it to specify the measure of similarity, the dimension of vectors to be stored in the index, the numbers of replicas to use, and more.
The Delete operation deletes vectors, by id, from a single namespace. You can delete items by their id, from a single namespace.
The Fetch operation looks up and returns vectors, by ID, from a single namespace. The returned vectors include the vector data and/or metadata.
The Query operation searches a namespace, using a query vector. It retrieves the ids of the most similar items in a namespace, along with their similarity scores.
The Update operation updates vector in a namespace. If a value is included, it will overwrite the previous value. If a set_metadata is included, the values of the fields specified in it will be added or overwrite the previous value.
The Upsert operation writes vectors into a namespace. If a new value is upserted for an existing vector id, it will overwrite the previous value.
(30 seconds)
(10 seconds)
(30 seconds)
(10 seconds)
(2 minutes)