Warmbox.ai
MailReach.co
Warmup Inbox
Mailwarm
Folderly
Murlist Email Warmup
MailChimp
Email Warmup by GMass
Qdrant
Milvus
Weaviate
pgvecto.rs
Vespa.ai
txtai
Zilliz
ElasticSearch
Warmbox help you to warm up your cold email inbox to never land in spam anymore 🎉
How does it work? Warmbox algorithm interacts automatically with your inbox, as humans, in order to increase your deliverability. Connect Warmbox to your inbox in seconds. Warmbox will send emails from your inbox. Remove these emails from the Spam folder. Open your emails. Bookmark your emails. Reply to your emails. Your inbox gets warm. Your emails don't land in spam anymore.
Want to give a try? 👉 https://warmbox.ai/
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.
Using Warmbox since few months and work like a charm! Got no email landing in spam now, recommend at 100%
Thanks to the team 🎉
The best tool around after trying most of email warm-up software!
Based on our record, Qdrant should be more popular than Warmbox.ai. 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'm really happy to announce to you that I'm launching a new product around email deliverability: Warmbox.ai, one of the most advanced email warm-up tool that helps you to never land in spam. On ProductHunt, today! Source: about 3 years ago
By the way, I'm really happy to announce to you that we're launching a new product around email deliverability: Warmbox.ai, the most advanced email warm-up tool that helps you to never land in spam. On ProductHunt, today! It integrates natively the Mailook feature for, so you can check your deliverability for free inside it! Source: about 3 years ago
Hello guys! 😃 We are launching on PH today Warmbox.ai to help anyone to warm-up your inbox and never land in spam anymore! Source: about 3 years ago
Interested in warmbox.ai bro. Did you try its alternatives? Mailwarm or mailreach? Source: over 3 years ago
Vector Databases: Qdrant for efficient data storage and retrieval. - Source: dev.to / 8 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 2 months 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 / 3 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.
Warmup Inbox - Warmup Inbox is a tool that automates the process of warming up your email inboxes, raising your sender reputation and inbox health automatically.
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