Amorce StudioBuild an App with Advanced Search
Users expect search to just work — fast, relevant, and forgiving of typos. Amorce Studio builds AI-powered apps with search that go beyond basic keyword matching to deliver genuinely useful results. Our AI agents implement full-text indexing, fuzzy matching, faceted filters, and relevance tuning tailored to your content. Whether your app catalogs products, articles, user profiles, or documents, we build search experiences that help users find exactly what they need in milliseconds, turning a utility feature into a competitive advantage.
Create Your App< 80ms
Average search response time across client apps
28%
Typical increase in conversion from improved search
99.5%
Queries returning relevant results with fuzzy matching
What You Get
Full-Text Indexing
Every searchable field is indexed for instant retrieval. Our AI agents configure text analyzers with stemming, synonym expansion, and stop-word removal so searches return relevant results regardless of exact phrasing.
Fuzzy Matching
Typo tolerance ensures users find what they want even with misspelled queries. Levenshtein distance matching and phonetic algorithms catch common mistakes without returning irrelevant noise in the results.
Faceted Filtering
Let users narrow results by category, price range, date, location, or any custom attribute. Facet counts update dynamically as filters are applied, giving users clear feedback about available options.
Autocomplete Suggestions
Search-as-you-type suggestions appear within milliseconds, guiding users toward popular queries and existing content. Suggestion ranking considers query frequency, recency, and the individual user's search history.
Relevance Tuning
Results are ranked by configurable relevance factors — not just text match, but recency, popularity, user context, and business rules. Boost important content or demote outdated items without changing the search algorithm.
Search Analytics
Track what users search for, which results they click, and where they find no results. These insights reveal content gaps, navigation problems, and feature requests directly from user behavior.
Real-World Examples
An e-commerce platform with 15,000 products needed search that understood product attributes and customer language. Amorce Studio built an app with search using Meilisearch, with custom synonym dictionaries, attribute-based faceted filtering, and typo-tolerant autocomplete — increasing search-to-purchase conversion by 28 percent compared to the previous basic keyword search.
A knowledge base application for a software company needed to search across 5,000 technical articles, API documentation, and community posts. We implemented full-text search with code-aware tokenization, section-level ranking, and highlighted snippets — helping developers find answers 3x faster and reducing repetitive support tickets by a third.
A recruiting platform required fuzzy search across candidate profiles, skills, and experience descriptions. Our AI agents built a search system with skill synonym expansion, location-based filtering, and weighted scoring that prioritized recent experience — enabling recruiters to find qualified candidates in seconds instead of manually scanning through hundreds of profiles.
How It Works
Understand Your Search Needs
We analyze your content types, data volume, and user expectations to design the right search architecture. Our AI agents recommend whether Elasticsearch, Meilisearch, or database-level full-text search best fits your requirements, balancing search quality, infrastructure cost, and operational simplicity for your team's capacity.
AI Agents Build the Search Engine
Our AI agents generate the complete search pipeline: index configuration with custom analyzers, data synchronization from your primary database, query parsing with filter extraction, and a responsive front-end search interface. Every component is tuned for your specific content — product catalogs get different treatment than blog articles.
Refine and Improve
After launch, search analytics reveal how users interact with your search feature. We use click-through data and zero-result queries to refine relevance scoring, add missing synonyms, and surface content that users expect but cannot find. Your app with search gets smarter over time based on actual usage patterns.
Why Amorce Studio for Your App with smart search
Search is often the fastest path to conversion. Users who search are signaling high intent — they know what they want and expect your app to deliver it immediately. Amorce Studio builds apps with search that honor that intent, returning relevant results in under 100 milliseconds with intelligent ranking that puts the most useful content at the top.
Building search that feels good is harder than it looks. Simple database queries break down as content grows, and bolting on a search engine without proper configuration produces confusing results. Our AI agents handle the nuances: custom tokenizers for your domain vocabulary, language-specific stemmers, and synonym dictionaries that understand your industry's terminology.
Zero-result pages are conversion killers. When a user searches and finds nothing, they leave. Amorce Studio's search implementations include fallback strategies — relaxed matching, spelling suggestions, and category redirects — that minimize dead ends. Combined with search analytics, you gain a feedback loop that continuously improves the discovery experience.
Frequently Asked Questions
Which search engine do you use?
We choose the best engine for your needs. Meilisearch for fast, typo-tolerant product search. Elasticsearch for complex aggregations and large datasets. PostgreSQL full-text search for simpler applications. Our AI agents recommend the optimal solution based on your data volume and query complexity.
Does search work with multiple languages?
Yes. We configure language-specific analyzers with appropriate stemming, stop words, and Unicode normalization. Multi-language indexes support applications serving global audiences with accurate results regardless of the user's language.
How fast is the search?
Our search implementations typically return results in under 100 milliseconds, including network latency. Autocomplete suggestions appear in under 50 milliseconds. For very large datasets, we use index sharding and query caching to maintain speed.
Can I control which results appear first?
Absolutely. We implement configurable relevance tuning that lets you boost or bury results based on business rules — promote featured products, prioritize recent content, or suppress out-of-stock items. Changes take effect immediately without reindexing.
What happens when search returns no results?
We implement progressive query relaxation that broadens the search when exact matches fail. Users see spelling suggestions, related categories, and popular items in their context. Analytics track zero-result queries so you can address content gaps systematically.