See how AI works
in Retail

Basket analysis took five months to build. Now, marketers use conversational AI to segment customers and launch campaigns instantly.

Narrating intricate work meant late-night shoots. She now films hands separately and overlays an AI avatar to deliver the lecture.

Rising costs held back AI scaling. Now, optimized GPUs power agents that generate design prototypes in seconds, not weeks.

Updates under 30 lines sat for 65 hours. Gemini now auto-approves safe changes, saving 70k developer hours monthly.

Exact-match search missed synonyms. AI now maps intent—linking "cooling goods" to inventory—turning vague queries into sales.

IT reporting took 10 mins while shoppers waited. AI now captures tickets via voice or text, cutting resolution time from 2 hours to 30 mins.

Manual reviews for artisan products took days. Gemini now generates listings from a single image, cutting approval to <1 hr.

Data scattered across systems forced manual consolidation. Now, AI unifies insights to trigger personalized campaigns instantly.

Manual categorization delayed revenue. Staff-built agents now auto-classify products for 91% faster onboarding, with human oversight.

300+ receipt layouts forced manual entry. GenAI now reads raw images with 98.6% accuracy, cutting costs 90%.

Classifying 100 comments took an hour, forcing sampling. Llama 3.3 now sorts every review by issue type to prioritize fixes.

Logistics delays triggered 40k inquiry spikes. An AI agent now resolves 10,000 monthly cases across five languages.