SOLUTION

E-COMMERCE AI SUITE

Complete discovery and monetization stack for e-commerce with dynamic inventory — grocery, q-commerce, marketplaces. One API, one contract, one personalization layer

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BUILT FOR GROCERY · Q-COMMERCE · MARKETPLACES · ONLINE RETAIL

SEARCH · RECOMMENDATIONS · SMART PROMO

+12%

GMV Uplift

<1%

Empty results

+15%

Retention

1–3 wks

To Go Live

FULL E-COMMERCE AI SUITE IN ONE API

Instead of buying Search, Recommendations, and Smart Promo from different vendors, you get one end-to-end stack: one API, one attribution model, one contract

Search

AI-powered search that automatically increases conversion. Reduces zero-result queries to 1% and keeps shoppers on your site. Understands natural language, handles typos, and delivers relevant results from day one. Handles complex, conversational queries naturally

Recommendations

ML algorithms for product recommendations to increase average order value. Real-time personalization — every customer sees products most relevant to them. Works across home, product pages, cart, and in-search

Smart Promo (Merchant)

Smart merchandising control. Promote private label, promotional, and high-margin products in both search and recommendations. Full retailer control through dashboard. Never sacrifices relevance

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AI-POWERED ECOMMERCE WITH DYNAMIC INVENTORY

Grocery & Q-Com

Online supermarkets: 10,000–100,000 SKUs
Express / dark store delivery platforms
High-frequency stock updates (minutes, not days)
Diet-aware and occasion-based queries
Locality-specific assortments per warehouse

Marketplaces

Multi-seller catalogs: 100K–10M+ SKUs
Seller-driven inventory and pricing volatility
Cross-category and long-tail query handling
Seller quality signals in ranking
Sponsored product blending without relevance loss

Online Retail

Pharma, electronics, home goods, sports, fashion
Image-based search and recommendations
Seasonal assortment swings and clearance handling
Cross-sell and bundle-aware results
Multi-language & regional catalog support

QUERY › UNDERSTANDING › RESULTS

See how the system interprets real shopper queries, from simple product lookups to complex intent-driven and conversational searches. Live product demo available

«lactose-free milk»

UNDERSTANDS

Lexical match on «milk» + semantic expansion to «lactose-free», «lactose intolerant», dairy-free alternatives. Attribute filter applied automatically.

RESULTS

In-stock lactose-free SKUs first, ranked by conversion rate. Dairy alternatives surfaced as secondary results.

«healthy snacks for kids»

UNDERSTANDS

LLM classifies as intent query (not a product name). Decomposes into: low-sugar, child-appropriate, snack category. No-added-sugar attribute applied.

RESULTS

Fruit bars, rice cakes, yogurt pouches — ranked by age-appropriate signals and in-stock status. Empty result rate: 0%.

«what to cook for dinner»

UNDERSTANDS

LLM agent classifies as conversational / recipe query. Routes to multi-step resolution: identifies meal categories, maps to ingredient clusters available in current stock.

RESULTS

Meal suggestions with grouped ingredient sets — pasta, rice dishes, stir-fry — all filtered to available inventory. LLM generates guided response, not a raw product list.

«cheap protein powder no artificial»

UNDERSTANDS

Multi-attribute decomposition: protein powder (category) + price-sort + no artificial ingredients (attribute filter). Semantic ranking used for attribute matching.

RESULTS

Clean-label protein SKUs sorted by price ascending. Out-of-stock items suppressed. Alternative brands included if primary brand unavailable.

«something for a birthday party»

UNDERSTANDS

LLM agent identifies occasion query. Maps to clusters: cakes, candles, snacks, drinks, decorations. Pulls from current stock per cluster.

RESULTS

Organized result set by occasion category, with "Add all to cart" groupings. Guided conversational response explaining categories chosen.

ONE PLATFORM INSTEAD OF THREE VENDORS

Most retailers piece together search, recommendations, and retail media from different vendors — three contracts, three integrations, three sources of truth. Yango Tech replaces all of them

Search
Alternatives

These platforms were built for content discovery and retrofitted for e-commerce. Yango Tech was built inside Yandex Lavka, where search drives 42% of GMV across 1M+ SKUs.

Your shoppers get results based on what's actually in stock right now — not yesterday's index

Recommendations Alternatives

Buying recommendations from a separate vendor means managing two ML systems that don't share signals. Yango Tech unifies search and recommendations into one platform with shared behavioral data.

Better personalization, faster setup, one team accountable for the entire shopping experience

Retail Media
Alternatives

Standalone retail media platforms create attribution gaps because they live outside your core search and recommendations. Yango Tech builds retail media on the same foundation.

Sponsored placements that maintain relevance — and revenue attribution that actually adds up

In-House
Build

Building from scratch costs 18-24 months and a senior ML team that most retailers can't hire. Yango Tech delivers a battle-tested stack used by Yandex Lavka, Deli, and Alma — integrated in 2-4 weeks.

Skip the build phase entirely and start measuring revenue impact in week one

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