conversion rate uplift
less abandoned search sessions
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?


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.


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.


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.


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


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.


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.


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.


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.


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

+$100M incremental value
Modernized search platform for a iconic footwear brand
Grid Dynamics modernized the search platform with semantic search, engagement-based ranking and smart autocomplete capabilities. The enriched results relevance improved conversion rates across all channels, while the neural search approach based on deep learning proved especially efficient for complex queries, cutting zero results and further uplifting conversions.
+80% results relevancy improvement
Semantic search for a leading chemical marketplace
Grid Dynamics implemented and integrated a new semantic search platform. Query expansion using knowledge graph and special query parsing techniques greatly improved domain-specific query understanding. The new solution showed 92% (80% uplift) relevant results on the first page, and the click-through ratio increased by 30%, indicating high relevance of provided results.
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+15% mobile CTR improvement
Real-time recommendations for a tier-1 US retailer
Grid Dynamics developed, trained and deployed 40+ real-time session-aware models to learn and utilize session intent in recommendations. The models were deployed across all recommendation zones, and achieves a good balance between optimizing the click-through rate and the conversion rate. The recommendation system supports 1200 requests/second with low latency.
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Our latest innovations in search

Boosting product discovery with semantic search
Semantic search departs from traditional ways of matching and counting words and focuses on matching concepts. Its advanced techniques allow it to improve precision compared to full text search without worsening its recall.
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Enhance customer experience with Multi-Language Semantic Search
It is no longer enough to offer English-only search, and leading service providers are capitalizing on multilingual semantic search to offer their customers a more personalized, convenient experience, resulting in higher conversion and retention rates.
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Search platforms in AWS
Leverage AI-powered, open-source semantic search, neural search, visual search, AI recommendations, searchandising, search personalization, and smart autocomplete capabilities on AWS OpenSearch Service for one of the most comprehensive and cutting-edge search solutions in today’s digital age.
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Accelerate your AWS OpenSearch Service journey

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