10%
conversion rate uplift
25%
less abandoned search sessions
20%
CTR improvements
Migrate to AWS OpenSearch Service with us
Every retail environment is unique, with specific search solution requirements and customer experience needs. In order to get maximum ROI, faster speed-to-market and optimal value out of your retail search solution, you need a trusted partner with deep retail search expertise, optimized integration methodologies and AWS specific experience. Grid Dynamics has unique experience working with the AWS OpenSearch Service team, and developed the AWS Opensearch Starter Kit to make the implementation of best-in-class, open-source search solutions fast, efficient and seamless. Get started quickly with data ingestion and change streaming pipelines, integration with clickstream data, data quality framework, search results comparison tools, and much more. The AWS OpenSearch Starter Kit includes all the building blocks necessary to implement a modern, open source search solution that meets the needs of your business and the demands of your customers.
Why choose the AWS OpenSearch Starter Kit?
WORLD-CLASS DISCOVERY SOLUTIONS EXPERTISE
Over a decade of experience with tier-1 customers
In the last 10 years, we designed and implemented numerous product search, catalog navigation and recommendations solutions for leading retailers and brands. Our customers enjoyed double-digit improvements in click-through-rates and order conversion rates.
BATTLE-PROVEN IMPLEMENTATION APPROACH
Move faster while keeping the risks under control
Our battle-proven integration blueprint help achieve the smoothest and fastest upgrade of search experience across all channels.
We provide all the necessary analysis, customizations, performance and relevance tuning to help retailers connect customers with products they love.
DATA INGESTION SIMPLICITY
Make the most out of your data
Every search solution journey starts with data. Our starter kit has a pre-configured and ready-to-use data ingestion pipeline that seamlessly ingests your catalog and customer behavior data into the AWS OpenSearch Service. We can connect to most popular databases and storage systems, as well as to custom systems or multiple data source combinations.
The starter kit is able to cover not only basic cases but complex logic of primary / variant product transformation and is easily extensible to add new data transformation and enrichment functions.
MANAGE & ACCELERATE INTEGRATION PROCESSES
Ensure quality integration and optimal performance results
Monitor the integration process and analyze results on the fly with a comprehensive set of tools, including a data quality framework, value comparators and a detailed reporting feature that flags invalid data. Easily switch between different test frameworks, achieve data completeness and sanity validation, tune in the transformation configuration, and compare the results, all from one simple-to-use system.
All components are built to allow for quick customer-specific business logic customization, saving a significant amount of time compared to an integration from scratch.
AWS OpenSearch Service features
COMPREHENSIVE SEARCH SOLUTIONS
All you need to start your AWS OpenSearch implementation
We leverage AWS OpenSearch Service capabilities to easily ingest, secure, search, aggregate, view, and analyze data for enterprise search. OpenSearch provides a highly scalable system for providing fast access and response to large volumes of data with an integrated visualization tool, OpenSearch Dashboards, that makes it easy for users to explore their data. OpenSearch is powered by the Apache Lucene search library, and it supports a number of search and analytics capabilities such as k-nearest neighbors (KNN) search, SQL, Anomaly Detection, Machine Learning Commons, Trace Analytics, full-text search, and more.
SEMANTIC QUERY GRAPH
Retrieve the most relevant results
A semantic query graph is a uniform, extendable and human-readable way to represent query interpretation and normalization results, and to organize query processing steps into a pipeline. Leveraging this representation, our search solution can create a high-precision query for the OpenSearch engine to retrieve the most relevant results.
NEURAL SEARCH
Make sense of complex queries
Neural search leverages deep learning models to encode both queries and products as semantic vectors and represents them in such a way that similar products and queries are clustered together, where nearest neighbors are the most relevant matches. Our search solution provides all essential capabilities to train and run deep learning encoders and vector indexes for neural search.
RELEVANCY TIER RANKING
Rank results according to relevancy
Semantic query understanding enables splitting search results into relevance tiers. Additional ranking happens inside those relevance tiers, which prevents irrelevant items appearing in the top results. Our search solution combines multiple rankers based on rules and business signals with AI models such as wisdom of the crowd, personalization models and session intent models.
CONCEPT-ORIENTED ANALYTICS
Identify trends and optimize search
Semantic query understanding opens opportunities for concept-oriented query analytics, helping to identify trending concepts, data gaps and unrecognized terms, and to guide search relevance tuning efforts. Integration with customer engagement signals can also identify overexposed and underexposed content and perform corrective actions.
Search Case Studies
Our Latest Innovations In Search
Accelerate your AWS OpenSearch Service journey
Workshops
We offer free half-day workshops with our top experts in AWS OpenSearch Service to discuss the benefits of migration, our strategic approach, and how to apply it in your environment.
Proof of concept
If you’re interested to see AWS OpenSearch Service in action, we can start with a 1-2 week proof-of-concept project to demonstrate the quality and performance of AWS OpenSearch in your business environment.
Discovery
If you’re at the stage of business requirements analysis and strategy development, we can start with a 2-3 week discovery phase to help develop the business case, design an optimized solution and build an implementation roadmap.
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