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Your stack retrieves products. searchHub makes discovery learn and improve.

A powerful site search engine is not a self-improving system. Modern platforms retrieve products quickly, apply business rules, and support complex experiences. But they still depend on the quality of the input, catalog data, configurations and manual decisions they receive.

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YOUR STACK DOES NOT AUTOMATICALLY KNOW:
where shoppers are quietly losing their way.
Which different queries express the same intent.
Why a result set underperforms.
Which destination best serves a particular need.
Whether an optimization actually worked.
Detect the opportunity. Apply the improvement. Measure the outcome. Learn from the result.
Built differently
Inside your infrastructure, or ours

Run the query rewriting next to your engine, and your shopper never waits on a round trip to our cloud.

Non-critical by design

If searchHub is unavailable, your engine still answers every search. With the query rewriting in your infrastructure, optimization keeps running too, from its last update.

Outside the API meter

Your search volume isn't turned into a per-query searchHub bill.

The result: AI-powered optimization without replatforming, runtime dependency or request-based economics.
No API bottleneck. No API dependency. No per-query pricing.

What searchHub adds to every stack

A complete view of discovery performance:

interactions connected across the whole journey and mapped to underlying intent, revealing weak experiences invisible to event-level analytics.

Cleaner intent before retrieval:

variations grouped, intent shaped as shoppers type. Better input produces more consistent output.

Automated action at scale:

detected opportunities become intent-aware suggestions, query rewriting, routing and redirects. No more fixing every recurring issue by hand.

Ranking grounded in outcomes:

Your catalog says what a product is. Shopper behavior shows which products people actually buy. searchHub ranks by what converts, not just by text or vector similarity.

Neural intelligence without neural replacement:

stronger results infused selectively where they create measurable value, without the cost, latency and complexity of live inference on every request.

Continuous proof:

every change is A/B-tested against real user behavior and business outcomes. Changes that don't measurably improve results are rolled back.

Engine-agnostic by design

A future-proof layer for a changing stack

When discovery intelligence is locked inside one engine, migrating means losing years of configurations, assumptions and behavioral knowledge. searchHub separates the understanding of shopper intent from the underlying retrieval technology. Change the engine without losing the intelligence. That makes searchHub the one constant in search and product discovery: it outlasts a re-platforming. After a few weeks of learning on the new engine, the agent picks up where it left off, because every engine, however good, still has more to give.

The intelligence stays
searchHub
FactFinder
Algolia
Elasticsearch
Keep the engine. Replace the query.

Everything you preserve

The existing search engine. The commerce platform. Catalog and product feeds. Filters and facets. Merchandising rules. Curated results. Business logic. The established front-end experience. Infrastructure, data ownership, and platform sovereignty.

One additional layer, value across teams

Search & merchandising: less repetitive query maintenance, full control over ranking, curation, and business priorities.
Product & ecommerce: see where discovery loses customers; prioritize by measurable business potential.
Data & AI: structured first-party intent signals that improve analytics, recommendations, models, and assistants.
Engineering: better discovery without replacing proven infrastructure. Engine-agnostic; it accelerates the roadmap rather than blocking it.
Business leaders: higher return on existing search and commerce investments, lower cost and risk of continuous optimization.
The learning loop
Detect the opportunity.
Apply the improvement.
Measure the outcome.
Learn from the result.

Make a capable stack continuously better.

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