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.
Intercom provides a lot of value to us. From live chat to email marketing and even helping us to create support documentation, Intercom handles a lot of key moving parts that are essential to keeping customers happy.
Based on our record, Qdrant should be more popular than Intercom. 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.
Vector Databases: Qdrant for efficient data storage and retrieval. - Source: dev.to / 5 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
Use chatbots to automate customer service: Chatbots use natural language processing to communicate with customers and answer their questions. By integrating chatbots into your affiliate marketing strategy, you can automate customer service and increase engagement with potential customers. This can lead to more sales and higher commissions. (Crisp, Intercom). Source: over 1 year ago
I am trying to create an application that will work on a customer's website. Much like tawk.to or intercom.com. Source: about 2 years ago
My way of doing marketing starts with figuring out what my overall project will (or will not) be. In this case, I looked at the vendors like Zendesk, Intercom, Freshdesk, or Help Scout. They all have whizbang features such as live-chat, collaboration stuffs, automations and workflows. They bill per contact and addons. I’d emphasize a straightforward, fuss-free angle instead. Source: about 2 years ago
I wanted to know the best practices of developing a widget. So I went through the popular implementations of it. I liked Intercom's widget very much. It is written in React. I analyzed how it works. The minimal javascript is loaded async on the webpage. It is injecting an iframe with id intercom-frame. That iframe has a script in it's head with a source URl. Obviously it is React bundle. Source: about 2 years ago
If you're looking at it to guide new users through onboarding, Intercom is pretty good. Source: about 2 years ago
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