Warmup Inbox
MailReach.co
Warmbox.ai
Mailwarm
MailChimp
Folderly
Brevo
ListKit.io
Qdrant
Milvus
Weaviate
pgvecto.rs
Vespa.ai
txtai
Zilliz
ElasticSearch
The process of preparing an email address for general use or email outreach is commonly referred to as “Warming Up” an inbox, where you take a number of steps to ensure that an email address does not become deactivated, blacklisted, or automatically marked as spam when it begins to send outgoing messages to other recipients.
Warming Up an email inbox essentially is recreating the way a typical person will use an email address. Just by using your email address normally, you are ‘warming up’ your inbox by sending outgoing mail to other existing users. When you are reading your emails, starring/favoriting certain messages, and engaging in email threads with multiple other email addresses, you are building up your domain reputation in a way that shows that your account is being controlled by a real human being and is not being used to send out unsolicited emails that are trying to mislead/scam/defraud any other real people using their email inbox.
Qdrant is a leading open-source high-performance Vector Database written in Rust with extended metadata filtering support and advanced features. It deploys as an API service providing a search for the nearest high-dimensional vectors. With Qdrant, embeddings or neural network encoders can be turned into full-fledged applications. Powering vector similarity search solutions of any scale due to a flexible architecture and low-level optimization. Qdrant is trusted and high-rated by Machine Learning and Data Science teams of top-tier companies worldwide.
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Qdrant's answer:
Advanced Features, Performance, Scalability, Developer Experience, and Resources Saving.
Qdrant's answer:
Highest performance https://qdrant.tech/benchmarks/, scalability and ease of use.
Qdrant's answer:
Qdrant is written completely in Rust. SDKs available for all popular languages Python, Go, Rust, Java, .NET, etc.
Based on our record, Qdrant should be more popular than Warmup Inbox. It has been mentiond 40 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I went to mail-tester.com to check the spamminess of my email and it comes back as a 4.4/10 and says that I should consider myself lucky if my emails go to primary inbox. Is there any way to solve this? Does a tool like warmupinbox.com solve a lot of these problems? Source: over 1 year ago
I'm also using warmupinbox.com with the same email address and see no problems. Source: over 1 year ago
Join this warmup tool it is 9 buscks a month and will improve your domain at least for other providers, I dont think it will help with outlook tho. https://warmupinbox.com im one week sending and receiving about 50 emails a day. Source: over 2 years ago
You can also use a warm up service like https://warmupinbox.com/ for 9 bucks a month will improve your domain reputation. Source: over 2 years ago
Vector Databases: Qdrant for efficient data storage and retrieval. - Source: dev.to / 4 days ago
AgentCloud uses Qdrant as the vector store to efficiently store and manage large sets of vector embeddings. For a given user query the RAG application fetches relevant documents from vector store by analyzing how similar their vector representation is compared to the query vector. - Source: dev.to / about 1 month ago
Great. Now that we have the embeddings, we need to store them in a vector database. We will be using Qdrant for this purpose. Qdrant is an open-source vector database that allows you to store and query high-dimensional vectors. The easiest way to get started with the Qdrant database is using the docker. - Source: dev.to / about 1 month ago
I took Qdrant for this project. The reason was that Qdrant stands for high-performance vector search, the best choice against use cases like finding similar function calls based on semantic similarity. Qdrant is not only powerful but also scalable to support a variety of advanced search features that are greatly useful to nuanced caching mechanisms like ours. - Source: dev.to / about 2 months ago
I'm currently looking to implement locally, using QDrant [1] for instance. I'm just playing around, but it makes sense to have a runnable example for our users at work too :) [2]. [1]. https://qdrant.tech/. - Source: Hacker News / 2 months ago
MailReach.co - The #1 email warming service to improve your deliverability by generating realistic and meaningful engagement to your emails. Easy-to-use solution to help you land in the main inbox instead of the spam folder.
Milvus - Vector database built for scalable similarity search Open-source, highly scalable, and blazing fast.
Warmbox.ai - Warm up your cold email inbox, and never land in spam anymore!
Weaviate - Welcome to Weaviate
Mailwarm - The email warm-up tool.
pgvecto.rs - Scalable, Low-latency and Hybrid-enabled Vector Search in Postgres. Revolutionize Vector Search, not Database. - tensorchord/pgvecto.rs