What Constructor does
Constructor is an AI-native commerce discovery platform for search, browse, recommendations, collections, retail media, enrichment, and shopper agents.
Constructor focuses on enterprise commerce discovery across search, autocomplete, browse, recommendations, collections, quizzes, retail media, attribute enrichment, and cross-channel experiences. Its AI Shopping Agent helps narrow early discovery through conversation, while Product Insights Agent answers product-detail questions and Merchant Intelligence Agent explains performance. The ranking system combines catalog metadata, context, shopper behavior, and reinforcement learning, aiming at commerce outcomes instead of generic text similarity. A headless API and client libraries let retailers control the final storefront.
Implementation begins with catalog mapping and behavioral instrumentation, not prompt writing. Product IDs, groups, variants, category hierarchy, attributes, prices, inventory, ratings, and displayable fields must be accurate. Search, browse, cart, and conversion events must identify the right item and user context. Missing or biased tracking can reinforce poor rankings, while generated enrichment or agent answers can invent compatibility and product claims. Retailers should require authoritative sources, hide sensitive metadata, distinguish sponsored products, enforce inventory and eligibility, test long-tail and multilingual queries, and provide low-confidence fallback.
Constructor does not publish a self-service price; enterprise buyers book a demo and receive a custom proposal. The quote should include selected products, catalog and event scale, peak request volume, environments, implementation support, SLA, retail media, agents, and overage. Constructor recommends phased launches and business or merchandising QA, which helps isolate value and risk. Procurement should also verify data retention, training use, subprocessors, residency, encryption, authentication, auditability, incident terms, and deletion or migration. Vendor case-study lifts are useful test hypotheses rather than guaranteed returns for another retailer.
How Constructor works
Constructor ingests catalog entities and verified clickstream events into separate indexes, then applies language understanding, transformers, behavioral learning, and merchant controls to rank search, browse, recommendations, and agent answers. APIs return results that the retailer tests, renders, and governs.
Map the product catalog
Constructor receives items, variations, groups, categories, attributes, facets, prices, inventory, and approved metadata through feeds, connectors, or APIs into environment-specific indexes.
Collect verified shopper behavior
Browser and server events describe search, browse, clicks, carts, and purchases with consistent identifiers and consent. The platform uses these signals to learn which products satisfy intent and business outcomes.
Return a governed discovery experience
Language models, transformers, reinforcement learning, context, and merchant rules rank search, browse, recommendations, collections, or agent answers. APIs let the retailer control final rendering and fallbacks.
Validate relevance before expansion
Engineering and merchandising test catalog claims, inventory, long-tail queries, segments, latency, sponsored placement, and customer outcomes against a control, then phase additional surfaces or agents into production.
How to set up Constructor
Baseline the current discovery experience
Measure query volume, zero results, reformulations, click and conversion, category engagement, recommendation performance, latency, and business constraints before changing the engine.
Map and validate catalog entities
Define items, variations, groups, categories, searchable fields, facets, displayable metadata, localized prices, inventory, eligibility, ratings, and fields that must remain private.
Implement verified behavioral events
Instrument search, browse, click, cart, purchase, and other approved events with consistent IDs, consent, deduplication, and test traffic separation so learning receives trustworthy signals.
Integrate one experience in staging
Create separate indexes, connect feeds or APIs, render search or browse through a client library, add merchandising rules and fallbacks, and test claims, relevance, access, and latency.
Run controlled QA and phased launch
Have merchandising and engineering review representative queries and segments, compare against a control, monitor drift and incidents, then add recommendations or agents only after evidence.
Constructor FAQs
What does Constructor do?
Constructor provides ecommerce search, browse, recommendations, collections, retail media, quizzes, attribute enrichment, and AI shopping or product-insight agents through a headless platform.
How much does Constructor cost?
Constructor uses custom enterprise pricing available through a demo and proposal. Buyers should include products, traffic, catalog scale, environments, services, SLA, and overage assumptions.
What data powers Constructor personalization?
Its documentation describes catalog data plus verified shopper clickstream signals across search, browse, recommendations, and conversion events, combined with context and merchant controls.
Can Constructor answer product questions?
Its Product Insights Agent can generate personalized answers, but retailers must ground responses in approved catalog content and validate compatibility, regulated, safety, price, and availability claims.
Can retailers control the ranking?
Yes. Constructor provides merchandising controls, rules, analytics, experiments, metadata configuration, and headless rendering. Teams should test overrides so commercial goals do not destroy relevance.
Listing reviewed 2026-07-15. Product details and pricing can change; verify important terms on the provider's website.
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