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E-commerce · The House of Things

How 9AI Cut Product-Search Time 96% for a Luxury Furniture Brand

96% Faster Product Discovery

The House of Things curates 30,000+ designer SKUs but clients arrive with mood-board images and vague briefs. Designers spent 18 minutes per search trawling Magento. 9AI deployed a CLIP-powered visual search platform that returned a ranked top-10 in under 60 seconds, recovered ₹7.5L per month in designer labour, and lifted cross-sell conversions from 8% to 26%.

96%

Search Speed

faster

₹7.5L

Monthly Labour Saved

26%

Cross-Sell Rate

from 8%

180h/wk

Designer Hours Freed

The new visual search lets us wow clients in minutes instead of spending half a day hunting for the right pieces.

— Head of Design, The House of Things

The House of Things is a Udaipur-based luxury marketplace for designer furniture, art, and lighting with 30,000+ SKUs from over 200 studios. Their sales model is consultative: clients share mood boards, architects send reference images, and designers are expected to produce curated shortlists instantly. The catalog is only searchable by keyword in Magento — useless when a client says "I want something like this" and shows you a photo.

The average shortlist took 18 minutes to assemble manually. At peak inquiry volumes, the design team burned 200 hours per week on search alone — ₹10L in monthly labour before a single recommendation was made. Slow responses on WhatsApp cost deals. Incomplete shortlists undersold the catalog. Cross-sell was almost never happening because designers had no bandwidth to surface complementary pieces.

#Before vs After: The Visual Search Impact

MetricBefore AIAfter AIChange
Search time per query18 minutes< 60 seconds96% faster
Designer search hours / week200 hours20 hours90% reduction
Monthly labour on search₹10L₹2.5L₹7.5L recovered
Search match accuracy70%95%++25 percentage points
Cross-sell conversion rate8%26%+18 percentage points
Search time per query
Before AI18 minutes
After AI< 60 seconds
Change96% faster
Designer search hours / week
Before AI200 hours
After AI20 hours
Change90% reduction
Monthly labour on search
Before AI₹10L
After AI₹2.5L
Change₹7.5L recovered
Search match accuracy
Before AI70%
After AI95%+
Change+25 percentage points
Cross-sell conversion rate
Before AI8%
After AI26%
Change+18 percentage points

#What 9AI Built

#The Visual Search Platform — 5 Components

1

Nightly Magento Catalog Sync

A pipeline pulls all active SKUs — product photography, attribute tags, descriptions — into the platform each night. No changes to Magento required.

2

CLIP Multi-Modal Embedding

Each product gets a vector that encodes visual appearance, material, form factor, colour, and era — not keyword tags. Image queries and text queries are encoded the same way.

3

PgVector Similarity Search

Top-10 nearest SKUs retrieved by cosine similarity in under one second from a 30,000+ product corpus. No scroll, no tabs.

4

Style-Affinity Upsell Layer

Complementary pieces ranked by visual style proximity surface automatically alongside the main results — replacing manual cross-sell guesswork.

5

WhatsApp-Native Delivery

Designers run searches and share shortlinks directly inside WhatsApp Business. Zero context switching; clients receive the shortlist without leaving the conversation.

#Questions About This Project

#Results at Month 4

96%

Search Speed

faster

₹7.5L

Monthly Savings

labour recovered

+18 pp

Cross-Sell Lift

8% → 26%

180h

Team Hours Freed

per week

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We help industrial companies become AI-native, from AI strategy and readiness to industry-specific Operating Systems and embedded implementation & adoption.

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Industries

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Company

AboutCase StudiesContactBlog

Resources

Media & NewsCareersCrunchbase
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