Modernize Your Search with OpenSearch
Transform your existing search platform into a cutting-edge, AI-powered search experience. Add semantic search, hybrid search, LLM-powered query understanding, and agentic RAG capabilities to deliver the modern search experience your users expect.
BigData Boutique's expert engineers, led by OpenSearch Ambassador Itamar Syn-Hershko, specialize in modernizing search platforms across industries. Whether you're running e-commerce search, real-estate directories, or knowledge-base software, we help you unlock the full potential of modern AI search technologies.
As AWS's top OpenSearch partner, we deliver secure, scalable solutions that maximize user satisfaction, conversion rates, and business outcomes through superior search experiences.
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Trusted By
13yrs
of Search Technology Experience
50%
Average Relevance Improvement
100+
Search Platforms Modernized
The Challenge
Traditional keyword-based search is no longer sufficient for modern applications. Users expect intelligent, context-aware search that understands intent, handles natural language queries, and delivers relevant results even when exact matches don't exist. Legacy search implementations struggle with synonyms, typos, semantic understanding, and complex query patterns.
Meanwhile, AI and machine learning have revolutionized what's possible with search. Semantic search, vector embeddings, hybrid ranking, and LLM-powered query understanding can dramatically improve search quality. However, implementing these technologies requires deep expertise in both search engineering and modern AI techniques—expertise that most organizations lack internally.
Modern Search
Capabilities
Semantic Search & Vector Embeddings
Move beyond exact keyword matching to understanding meaning and context. Vector embeddings powered by modern language models enable search results based on semantic similarity, dramatically improving relevance for natural language queries and finding results even when exact terms don't match.
Hybrid Search
Combine the precision of keyword search with the intelligence of semantic search. Hybrid search blends traditional BM25 ranking with vector similarity, delivering optimal results across diverse query types. Fine-tuned relevance weighting ensures the best of both approaches for your specific use case.
Advanced Relevance Tuning
Optimize search ranking with sophisticated relevance tuning strategies. Implement learning-to-rank models, personalized ranking, business rules, and click-through analytics to continuously improve search quality and align results with business objectives and user preferences.
LLM-Powered Query Understanding & Optimization
Leverage large language models to understand user intent, expand queries with synonyms and related terms, correct spelling errors, and optimize complex queries for better performance. LLM-powered query parsing can extract structured filters from natural language and handle conversational search patterns.
Agentic RAG Applications
Build intelligent Retrieval-Augmented Generation applications where AI agents can search, reason, and synthesize information from your data. Enable conversational interfaces, automated research assistants, and intelligent document analysis that goes far beyond traditional search capabilities.
Vector Search at Scale
Implement production-ready vector search capable of handling billions of embeddings with millisecond latency. Optimize HNSW indexes, manage embedding generation pipelines, and architect distributed systems that scale vector search to enterprise requirements without sacrificing performance.
The BigData Boutique
Solution
BigData Boutique, an AWS Advanced Consulting Partner with global expertise and 13+ years of search technology experience, offers comprehensive search modernization services. Our team combines deep search engineering expertise with cutting-edge AI/ML knowledge to transform your search platform.
We've successfully modernized search for e-commerce platforms, real-estate directories, knowledge-base software, and enterprise applications across diverse industries. Our proven methodology delivers measurable improvements in search quality, user satisfaction, and business metrics.
Search Assessment & Strategy
We analyze your current search implementation, user behavior, and business requirements. We identify opportunities for improvement, recommend appropriate AI technologies, and develop a strategic roadmap for modernization that balances quick wins with long-term transformation.
Implementation & Integration
Our experts implement semantic search, hybrid ranking, vector embeddings, and LLM-powered features tailored to your specific use case. We integrate seamlessly with your existing infrastructure, ensuring production-ready implementations with proper monitoring, scaling, and reliability.
Relevance Tuning & Optimization
We continuously optimize search relevance through A/B testing, user behavior analysis, and iterative tuning. Our data-driven approach ensures search results align with user intent and business objectives, with measurable improvements in key metrics like click-through rates and conversion.
Training & Knowledge Transfer
We ensure your team can maintain and evolve the modernized search platform. Through hands-on training, documentation, and best practices guidance, we transfer knowledge and build internal capabilities for ongoing search innovation and optimization.
Industry Solutions
E-Commerce Search
Transform product discovery with semantic search that understands shopper intent. Implement hybrid ranking that balances relevance with business rules, personalized recommendations based on user behavior, and intelligent query understanding that handles natural language product searches. Our e-commerce search modernization typically delivers 30-50% improvements in conversion rates through better product discovery.
Real-Estate Directories
Enable intelligent property search with semantic understanding of location descriptions, lifestyle preferences, and amenity requirements. LLM-powered query parsing extracts structured filters from natural language ("family-friendly neighborhood near good schools"), while vector search surfaces similar properties even when exact criteria don't match. Combine with geospatial search for comprehensive property discovery.
Knowledge-Base Software
Build intelligent knowledge discovery with semantic search across documentation, support articles, and internal wikis. Implement agentic RAG for conversational interfaces that can answer complex questions by synthesizing information from multiple sources. Vector search enables finding relevant content based on meaning, not just keywords, dramatically improving knowledge worker productivity and customer self-service success rates.
Our Modernization Approach
Discovery & Baseline Assessment
We begin with comprehensive analysis of your current search implementation, including relevance quality, user behavior patterns, and business requirements. We establish baseline metrics for search quality, performance, and business impact to measure improvements against.
Technology Selection & Architecture
Based on your specific use case and requirements, we recommend appropriate AI technologies and design the architecture for modernized search. This includes selecting embedding models, designing hybrid ranking strategies, planning LLM integration, and architecting for scale and performance.
Phased Implementation & Testing
We implement modern search capabilities in phases, starting with high-impact features and progressively adding advanced functionality. Rigorous A/B testing ensures each enhancement delivers measurable improvements before full rollout. This de-risks the transformation and enables continuous validation.
Optimization & Continuous Improvement
Post-launch, we continuously optimize search relevance through ongoing tuning, user feedback analysis, and iterative improvements. We establish processes and tooling for your team to maintain and evolve the search platform, ensuring sustained excellence and adaptation to changing requirements.
Why Choose BigData Boutique
Deep Search & AI Expertise
Our team combines 13+ years of search engineering experience with cutting-edge AI/ML expertise. Led by OpenSearch Ambassador Itamar Syn-Hershko, we understand both traditional search techniques and modern AI approaches, enabling us to architect optimal hybrid solutions.
AWS Partnership Benefits
As AWS's top OpenSearch partner with Service Delivery designation, we have early access to new features, direct relationships with AWS engineering teams, and deep knowledge of Amazon OpenSearch Service and AWS AI services like Bedrock and SageMaker.
Proven Results Across Industries
We've successfully modernized search for e-commerce platforms handling billions of products, real-estate directories serving millions of users, and enterprise knowledge bases spanning diverse content types. Our track record includes measurable improvements in relevance, conversion, and user satisfaction.
Production-Ready Implementations
We don't just build prototypes—we deliver production-grade implementations with proper monitoring, scaling, security, and reliability. Our solutions are battle-tested at scale and designed for long-term maintainability and evolution.
Ready to Transform Your Search?
Modern search technologies can dramatically improve user experience, increase conversion rates, and unlock new capabilities for your application. Whether you're starting fresh or enhancing an existing implementation, our experts can guide you through the journey.
Contact us to discuss your search modernization needs. We'll assess your current implementation, explore opportunities for AI- powered enhancements, and develop a roadmap for transforming your search platform.
Start Your Search Modernization
Schedule a consultation with our search experts to discuss modernizing your search platform. We'll analyze your current implementation, recommend appropriate AI technologies, and outline a path to transforming your search experience.