Search that users trust requires sub-50ms results, typo tolerance, and relevance tuning.
Algolia delivers the search experience that users have come to expect from best-in-class products: instant results, typo correction, faceted filtering, and the relevance tuning that surfaces the right results first. We implement Algolia for production applications.
Application with a slow or poor search experience — LIKE queries in Postgres, no typo tolerance, and relevance that doesn't match user expectations
Search is the feature that users rely on most heavily in content-heavy or inventory-rich applications. Poor search — slow results, no typo tolerance, poor relevance — drives users to competitors.
The Postgres LIKE query approach to search has fundamental limitations:
No typo tolerance. WHERE name LIKE '%shoes%' returns zero results for "shoees." Algolia handles typo correction automatically, returning relevant results even for misspelled queries.
Full table scan performance. LIKE '%query%' queries can't use standard B-tree indexes and require a full table scan. On tables with millions of records, this is seconds — not milliseconds.
No relevance ranking. SQL returns rows that match the query; it doesn't rank them by relevance. Algolia returns results ranked by a configurable relevance model that considers word position, attribute importance, and custom ranking criteria.
No faceted filtering. Filtering search results by category, price range, location, or other facets in SQL requires complex query construction. Algolia faceting is built in.
Algolia vs. Postgres full-text search: Postgres has full-text search via tsvector and tsquery. It's better than LIKE queries but still lacks typo tolerance, advanced relevance tuning, and the instant-as-you-type experience Algolia provides.
Algolia search integration with sub-50ms results, typo tolerance, faceted filtering, and the index configuration that surfaces relevant results
Index design
Records structured for Algolia indexing. Attributes defined for search, display, filtering, and ranking. Searchable attribute priority configured.
Indexing pipeline
Initial data sync from Postgres or other data sources to Algolia. Incremental index updates when records are created, updated, or deleted (via database triggers or application-level hooks).
Search UI
InstantSearch React components or custom search UI built on the Algolia JavaScript client. Instant-as-you-type search with debouncing. Highlighted results, pagination, and faceted filtering.
Relevance tuning
Custom ranking criteria. Business rules (promoted results, synonyms, stop words). A/B testing for relevance improvements.
Analytics
Algolia search analytics for query volume, no-results rate, and click-through rate. Used for ongoing relevance tuning.
One honest number to start.
Fixed-scope, fixed-price. The number below is the starting point — final scope is built from your brief.
Algolia search integration with sub-50ms results, typo tolerance, faceted filtering, and the index configuration that surfaces relevant results
Three steps, every time.
The same repeatable engagement on every project. No surprises, no mystery, no billable ambiguity.
Brief & discovery.
We send you questions, then get on a call. Output: a written scope with every step, feature, and integration listed.
Build & ship.
Fixed schedule, weekly reviews. No scope creep unless you change the scope — and if you do, we reprice it transparently.
Warranty & retainer.
30-day warranty on every launch. Most clients stay on a monthly retainer for ongoing features and maintenance.
Why Fixed-Price Matters Here
Algolia implementation scope is defined by the search requirements and the data model. Fixed price.
Questions, answered.
Algolia: managed, fast to implement, excellent DX, paid at scale. Elasticsearch/OpenSearch: open source, powerful, requires operational management. Typesense: open source Algolia alternative, self-hosted, good DX. For most product teams, Algolia is the right choice until the cost (based on records and search operations) exceeds what a managed service is worth.
Algolia charges per search request and per record. The free plan includes 10,000 search requests/month and 10,000 records. At scale, Algolia can become expensive — but the cost per user value of good search is high.
Search implementation is part of the application build. Full application with search from $28k. Fixed-price.
Tell Ryel about your project.
Describe what you’re building and what outcome you need. You’ll have a written, fixed-price scope within the week.