AI-powered Search

Overview

What we deliver

We implement AI-powered search that handles natural language queries, typos, and synonyms to return the most relevant results.

We replace rigid keyword search with AI-powered search that understands what users actually mean. Our approach combines vector embeddings, semantic matching, and traditional ranking signals so users find the right product, document, or article even when their query is vague or misspelled. We index your content, tune relevance, and add filters, facets, and sorting that match how people browse. For larger catalogs and knowledge bases, we add features like query suggestions, related searches, and zero-result recovery. We integrate the search experience into your website, app, or internal portal with clean APIs and front-end components. After launch, we review search analytics, fix poor performers, and keep relevance tuned as content and behavior change. The outcome is a search experience that feels intuitive, reduces bounce, and shortens the path from query to action.

Fit Check

Built for teams like yours

Who it's for

Ecommerce sites with deep catalogs
Publishers and content libraries
Knowledge bases and help centers
Internal portals and document repositories
SaaS apps with in-product search

Pain points we solve

Poor results for natural language queries
High zero-result rates on search
Users abandoning after weak matches
Hard-to-find documents in internal portals
Slow or clunky search experiences

What's included

Capabilities

Everything we cover in this engagement.

Search platform selection and setup
Content indexing and schema design
Vector embeddings and semantic search
Synonym, typo, and language handling
Faceted search and filters
Query suggestions and autocomplete
Analytics and relevance tuning
Front-end search components

How we work

Our process

A clear, predictable path from kickoff to outcomes.

01

Audit

We review current search performance and pain points.

02

Design

We plan the schema, ranking, and user experience.

03

Build

We index content, configure models, and build the UI.

04

Tune

We test queries, adjust ranking, and fix poor results.

05

Launch and refine

We deploy, monitor analytics, and tune over time.

What you get

Deliverables & outcomes

What you get

Configured search platform
Indexed content with mappings
Front-end search and filter components
Relevance tuning playbook
Search analytics dashboard
Documentation for content teams

Outcomes you can expect

Higher search conversion rates
Lower zero-result query rates
Faster time to find content
Better support deflection in help centers
Improved internal productivity

Timeline

6 to 10 weeks

Engagement

Monthly retainer, Project, Sprint

Tools we use

Elasticsearch, Algolia, Typesense, Pinecone, OpenAI embeddings

KPIs we track

Search conversion rate, zero-result rate, click-through rate, query refinement rate, time to result

Client stories

What clients say

"

Our old site was a Frankenstein of three previous agencies. We gave them a hard launch date tied to a trade show and they actually hit it. 47 templates, full product catalog migration, no broken redirects on go-live day. Our previous vendor missed the same deadline twice. This time my phone stayed quiet on launch morning.

Marcus L.

"

Holiday season was about to break us. We needed 22 agents in six weeks and our internal hiring pipeline could not move that fast. They staffed it, trained on our tone guide, and ran nesting alongside our senior reps. CSAT actually went up by three points during peak. First Q4 in four years my support lead took her vacation.

Tom H.

Proof