Swiftype Site Search
Algolia
ElasticSearch
Sumo
ChannelAdvisor
Site Search 360
Pure360
Klevu
Amazon Kendra
Algolia
ElasticSearch
Google Cloud Search
Curiosity.ai
Sinequa
Azure Cognitive Search
Apache Lucene
Swiftype Site Search Amazon KendraSwiftype Site Search is recommended for businesses of all sizes that want to implement an enhanced search experience on their websites. It is particularly beneficial for e-commerce platforms, content-rich websites, and companies with large amounts of data or products. Developers and website administrators looking for a customizable and scalable search solution will also find it advantageous.
Based on our record, Amazon Kendra seems to be more popular. It has been mentiond 9 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.
In today's AI-driven business landscape, chatbots have become the primary interface between companies and their customers. The effectiveness of these AI assistants hinges on one critical factor: the quality and accessibility of the data they're trained on. Amazon Kendra offers a powerful solution - a fully managed service that intelligently indexes and retrieves information from multiple data sources, enabling... - Source: dev.to / 2 months ago
The Q Business retriever is used to read the data from the index when users interact with the Q Business. You must specify the index type (in this example NATIVE_INDEX instead of using Amazon Kendra) and a reference to the index itself. - Source: dev.to / 10 months ago
I recommend you look deeper at LangChain if you are not already familiar with it. You can also look at the aws-samples Github page; they have some great examples to get you started. For example, you could add Amazon Kendra to the mix. Connect it with one of its many sources, like Atlassian Confluence, and set up Langchain to utilize the Kendra retriever. And now you have a chatbot that can answer questions based... - Source: dev.to / over 1 year ago
If you're doing this on AWS they already have a really contained solution for this. I'm sure Azure has a similar solution. I'll assume AWS - if so, AWS Kendra is a good place to start. This will give you performant natural language understanding and enterprise search support. Then you just need to map the rest of your desired functions to core AWS solutions. Source: about 2 years ago
> > One of the most important capabilities of Bedrock is how easy it is to customize a model. Customers simply point Bedrock at a few labeled examples in Amazon S3, and the service can fine-tune the model for a particular task without having to annotate large volumes of data (as few as 20 examples is enough) I can't even. Does anyone remember Amazon Kendra [1]? They promised the same there. "Here's an ML powered... - Source: Hacker News / about 2 years ago
Algolia - Algolia's Search API makes it easy to deliver a great search experience in your apps & websites. Algolia Search provides hosted full-text, numerical, faceted and geolocalized search.
ElasticSearch - Elasticsearch is an open source, distributed, RESTful search engine.
Sumo - Free tools to grow your email list.
Google Cloud Search - Search across all your company's content in G Suite.
ChannelAdvisor - As your partner in e-commerce success, we’re here to help you acquire more customers and land more sales than ever before. We keep our customers growing — and we have the stats to prove it.
Curiosity.ai - Find everything everywhere: Curiosity puts all your information at your fingertips so you can focus and get more done.