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features
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support

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Description

Amazon Kendra is an exceptionally precise and user-friendly enterprise search solution driven by machine learning technology. It provides robust natural language search functionalities for your websites and applications, allowing users to effortlessly locate the information they require amidst the extensive content available within your organization. By utilizing natural language inquiries rather than merely basic keywords, you can obtain the information you seek, whether it be specific answers, frequently asked questions, or complete documents. This eliminates the frustration of navigating through lengthy lists of links in hopes of finding relevant information. Say farewell to information silos, as Kendra enables seamless integration of content from various sources such as file systems, SharePoint, intranet sites, and file sharing services into a unified location, facilitating swift searches for optimal answers. Over time, the accuracy of your search results improves, thanks to Kendra's machine learning algorithms, which adapt to understand and prioritize the most valuable results for your users. This continual enhancement ensures that users consistently receive the most relevant and useful information with every search query they perform.

Description

Vectara offers LLM-powered search as-a-service. The platform offers a complete ML search process, from extraction and indexing to retrieval and re-ranking as well as calibration. API-addressable for every element of the platform. Developers can embed the most advanced NLP model for site and app search in minutes. Vectara automatically extracts text form PDF and Office to JSON HTML XML CommonMark, and many other formats. Use cutting-edge zero-shot models that use deep neural networks to understand language to encode at scale. Segment data into any number indexes that store vector encodings optimized to low latency and high recall. Use cutting-edge, zero shot neural network models to recall candidate results from millions upon millions of documents. Cross-attentional neural networks can increase the precision of retrieved answers. They can merge and reorder results. Focus on the likelihood that the retrieved answer is a probable answer to your query.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

AWS AI Services
Amazon Transcribe
Amazon Web Services (AWS)
BA Insight
Datavolo
IBM watsonx.data
Langflow
Microsoft SharePoint

Integrations

AWS AI Services
Amazon Transcribe
Amazon Web Services (AWS)
BA Insight
Datavolo
IBM watsonx.data
Langflow
Microsoft SharePoint

Pricing Details

$2.50 per hour
Free Trial
Free Version

Pricing Details

Free
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/kendra/

Vendor Details

Company Name

Vectara

Founded

2020

Country

United States

Website

vectara.com

Product Features

Enterprise Search

AI / Machine Learning
Faceted Search / Filtering
Full Text Search
Fuzzy Search
Indexing
Text Analytics
eDiscovery

Product Features

Enterprise Search

AI / Machine Learning
Faceted Search / Filtering
Full Text Search
Fuzzy Search
Indexing
Text Analytics
eDiscovery

Alternatives

Alternatives

Semantee Reviews

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