OpenSearch

With built-in capabilities of query semantic understanding and machine learning sorting algorithms for various industries, as well as fully open text vector search engine capabilities, it helps developers quickly build intelligent search services.

OpenSearch LLM-Based Conversational Search Edition is on public test.

New Features

LLM-Based Conversational Search Edition

LLM-based one-stop conversational search service

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Industry-Specific Enhanced Edition for E-Commerce

Industry-Specific Enhanced Edition for E-Commerce helps develop intelligent search services that provide higher performance, search efficiency, and search accuracy in the e-commerce industry.

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Vector Search and Multimodal Search

OpenSearch provides multimodal retrieval capabilities to optimize search efficiency and accuracy for customers from different industries.

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One-Stop Platform for Intelligent Search Service Development

OpenSearch is a one-stop platform to develop intelligent search services. OpenSearch was built based on the large-scale distributed search engine developed by Alibaba. OpenSearch serves more than 500 business cases in Alibaba Group and thousands of Alibaba Cloud customers. OpenSearch helps develop search services in different search scenarios, including e-commerce, O2O, multimedia, the content industry, communities and forums, and big data query in enterprises.

OpenSearch helps you develop high quality, maintenance-free, and high performance intelligent search services to provide your users with high search efficiency and accuracy.

Conversational search service

Build a dedicated conversational search system for enterprises based on the built-in large language model (LLM) and the business data of enterprises.

Search Practices in Multiple Industries

OpenSearch integrates the industry-specific knowledge graphs of Alibaba DAMO Academy, which helps develop industry-specific and intelligent search services in industry-specific search scenarios.

Search Algorithm Center

You can manage versions of algorithm models, iterate algorithm models, and train algorithm models based on data backflow in the search algorithm center.

Multimodal Retrieval

OpenSearch delivers high performance and reduces costs if you build vector indexes for a large amount of unstructured data, such as text, images, and behavioral data, and retrieve data based on the vector indexes.

Vector Search

Deeply integrated with Damo Institute's self-developed vector search engine Proxima to efficiently build vector search services, providing multimodal search for text/image/audio/video, etc.

Data Update within Millisecond

Thousand QPS millisecond query response

OpenSearch Scenarios

Conversational search service

The LLM-based conversational search service provides users with excellent search experience, efficiently improves the information acquisition efficiency, and increases the conversion rate of business.
OpenSearch LLM-Based Conversational Search Edition has the following benefits:

Dedicated conversational search services for enterprises
Builds dedicated conversational search services for enterprises based on business data. This makes conversation results more accurate and secure.

Multimodal search results
Supports multimodal search results such as answers, URLs, and images. This provides users with better search experience.

Low cost, easy to use
One-stop service that can be quickly connected. You can complete POC testing within 1 hour. The service is fully managed and O&M-free. You can use the service without deploying it.

Image Search

Images are typical unstructured data in AI field, which can carry more information, but cannot complete the retrieval by traditional split word recall.

Open Search vector search version can help customers abstract image data into vector features, build vector index based on the features, compare the vector data of the image under investigation with the vector index when querying, recall the vector with the closest distance to the image under investigation, and complete image retrieval.

Typical application scenarios include: image search (image search shopping, same price comparison), text search, photo search, image recognition, etc.

E-Commerce and O2O

The e-commerce and O2O scenarios have extremely high requirements for the retrieval and sorting of search results.

Better intent identification
The Industry-Specific Enhanced Edition for E-Commerce of OpenSearch provides industry-specific analyzers and a query analysis feature for better intent identification.

Common sort expressions for e-commerce
The Industry-Specific Enhanced Edition for E-Commerce also provides common sort expressions for e-commerce, which can meet sorting requirements without additional configurations.

Built-in algorithm models
OpenSearch provides built-in algorithm models for top searches, hints, and drop-down suggestions.

Content, Communities, and Forums

In the media industry, search keywords and content are diversified and may not follow word usage standards. In this scenario, intelligent semantic analysis is required.

OpenSearch allows customers in the content industry to customize models for term weight analysis, spelling correction, and query rewriting and identify the query intent using AI.

After algorithm tuning, popularity models can quantify the static quality and popularity degree of each commodity and generate popularity scores. This way, you can construct a more fine-grained sort model to meet your search requirements precisely.

Big Data Query in Enterprises

The data of enterprises involves multiple dimensions, and the data amount increases continually. In addition, enterprises require efficient data updates. In this scenario, a search engine that provides powerful capabilities and high performance is required.

The search engine of OpenSearch features auto scaling, simple syntax, convenient debugging, high stability, and cost-effectiveness.

OpenSearch can respond in seconds to the requests that search for updated data, which ensures data timeliness. OpenSearch also combines query analysis with intervention to better identify the query intent.

OpenSearch Features

Conversational search service

OpenSearch LLM-Based Conversational Search Edition helps enterprises quickly build a dedicated conversational search system based on the built-in LLM.

Dedicated conversational search services for enterprises

Build a dedicated LLM and conversational search system based on the business data of enterprises to ensure security, accuracy, high quality, and reliability.

Multimodal search results

Support multimodal search results such as answers, URLs, and images to meet specific search requirements of users.

Streaming output

Support streaming output that can provide faster conversation response and better user experience.

Develop Industry-Specific and Intelligent Search Services

OpenSearch adopts the Natural Language Processing (NLP) technology developed by Alibaba DAMO Academy to implement intelligent semantic understanding on search queries. You can customize sort policies for your intelligent search services based on your business needs.

Visualized Service Development

Provides visualized interfaces throughout the development of search services and comes with various templates for industries, such as e-commerce. You can implement all the features of search services without writing code.

Query Analysis

Adopts the NLP technology developed by Alibaba DAMO Academy to implement intelligent semantic understanding on search queries and provides the following capabilities based on intelligent semantic understanding: analysis, synonym configuration, spelling correction, stop word filter, term weight analysis, named entity recognition (NER), and category prediction.

Custom Sort Policies

Supports rough sort and fine sort and allows you to customize sort policies based on your business needs. You can use Cava-based sort plug-ins for exclusive applications to implement complex sorting.

Develop Search Guidance Services

OpenSearch provides common peripheral features to guide searches, such as drop-down suggestions, top searches, and hints. OpenSearch also provides algorithm services, such as popularity models and category prediction models. You can use the algorithm services to customize features and improve the quality of intelligent search services.

Drop-Down Suggestions

Customizes drop-down suggestions models based on the data pushed to applications, recommends candidate search queries to guide searches and provides extended features, such as blacklists, whitelists, and intelligent sorting

Top Searches and Hints

Customizes top search models and hint models based on the user search behavior, generates top searches and hints to guide searches, and provides extended features, such as blacklists, whitelists, and top search ranking

Algorithm Services

Provides intelligent search algorithm services, such as popularity models and category prediction models, to optimize sorting and allows you to customize algorithms for different features of a search service

Develop High-Performance Data Search Services

OpenSearch accelerates database queries based on the core search engine that Alibaba Cloud has developed for years.

Different Methods for Importing the Cloud and On-Premises Data Sources

Allows you to connect OpenSearch to ApsaraDB RDS, MaxCompute, and PolarDB data sources on Alibaba Cloud with a few simple steps and upload on-premises data on demand by using the OpenSearch API or OpenSearch SDKs.

Highly Efficient Data Update

After a number of documents are pushed to a standard application, 99% of the documents can be searched in one second. After a number of documents are pushed to the primary table of an advanced application, 90% of the documents can be searched in ten seconds.

Database Query Acceleration with High Performance

Accelerates database queries based on the core search engine developed by Alibaba Cloud and delivers four times the performance of open-source search engines

Vector Search Service

OpenSearch Vector Search Edition is designed for vector scenarios and helps enterprises build high-performance, low-cost, easy-to-use, and powerful vector search services.

High cost performance

The minimum specification can support 1 billion 128-dimensional vectors, or thousand QPS millisecond query response; support data compression, fine index structure design, non-all-memory loading method, effectively reducing memory overhead.

Rich vector capability

Support HNSW, QC and other vector retrieval algorithms; support mixed retrieval between label, text inverted index and vector index; support filtering by expression, with the ability to filter while retrieving.

Real-time writing of vector data

It supports real-time writing of vector data at high qps, real-time dynamic updating of indexes on-the-fly, and fast adjustment of cluster data storage limit.

OpenSearch Procedure

1

Create Instances

Purchase and create applications.

2

Configure Instances

Configure the data sources, index schema, and applications schema.

3

Develop Search Services

Develop search services based on industry-specific templates and optimize retrieval and sorting.

4

Effect Test

Run A/B tests to test the features of search services by routing a specific proportion of search requests to a test group before using the features in your online business.

5

Publish Search Services

View business reports and optimize operational strategies based on user experience.

Application Types

OpenSearch supports pay-as-you-go billing and subscription.

LLM-Based Conversational Search Edition



Suitable for enterprise customers who have requirements for dedicated conversational search services

Typical scenarios: internal knowledge base of enterprises, content communities and forums, and e-commerce shopping guide and after-sales service.

USD 0.030 per hour at least

Vector Search Edition



Suitable for enterprises and developers with large vector size and need for flexible development

Scenarios: Image Search, Personalized Search and Push, NLP Semantic Search

USD 0.543 per hour at least

General-purpose Edition for Exclusive Computing



Suitable for scenarios in which a large number of computing resources and a high-quality search service are required

Scenarios: Internet, E-commerce, and Retail applications

USD 28779.23 per year at least

Industry-specific Enhanced Edition for E-commerce



Suitable for the E-commerce and retail industries because of E-commerce-specific features

Scenarios: Commodity Search in the E-commerce and Retail Industries

USD 27952.53 per year at least

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