Teenva AI & Digital Ventures builds visual product search for fashion, home decor, furniture, and retail brands from Bangalore, India. Shoppers upload a photo or snap from camera—find this dress, sofa like this, matching tiles—and your Shopify store, WooCommerce site, or custom ecommerce platform returns visually similar SKUs from your catalog, ranked by embedding similarity plus stock, price, and category rules.
Visual search captures intent text search misses—patterns, silhouettes, and styles shoppers cannot name. It pairs with your product recommendation engine for shop-the-look carousels and feeds AI shopping assistant when users attach images in chat.
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Visual product search—image embeddings indexed to your catalog on web and mobile.
Hub: AI solutions · Domain: Ecommerce
How visual search works
| Step | What happens |
|---|---|
| 1. Input | User uploads JPG/PNG/WebP or captures via phone camera |
| 2. Preprocess | Crop, background removal (optional), quality check |
| 3. Embed | Vision model converts image to vector (CLIP-class or fine-tuned) |
| 4. Retrieve | Nearest neighbors in your product image index |
| 5. Re-rank | Stock, price band, category, margin rules |
| 6. Results | Grid of similar products with PDP links and add-to-cart |
Search runs against your SKUs only—not the open web or competitor catalogs.
Features we implement
- Multi-image catalog index — primary, alternate angles, lifestyle shots per SKU
- Fine-tuning (scoped) — domain-specific models for fashion, furniture, jewelry
- Hybrid search — combine visual similarity + text filters ("under ₹3k", "cotton")
- Region / object detect (scoped) — "Find this bag" in a full outfit photo
- Duplicate & variant merge — same product, different colors grouped sensibly
- Mobile-first UI — camera button in search bar on cross-platform app
- Widget embed — search bar icon on Next.js headless storefront
- Analytics — upload volume, click-through, conversion vs text search
- Index pipeline — auto-reindex on new products via Shopify/Woo webhooks
Where shoppers use it
| Surface | Experience |
|---|---|
| Header search | Camera icon next to keyword search |
| Category PLP | Search by photo for large visual catalogs |
| PDP | Shop similar from hero image |
| Inspiration pages | Click lookbook photo → similar in-stock items |
| WhatsApp (scoped) | User sends photo → bot returns product links via WhatsApp API |
| In-store kiosk (scoped) | Camera capture for showroom floor |
Architecture
Product images (PIM / Shopify / CDN)
Batch embedding + vector index (pgvector, Pinecone, etc.)
Query image → embed → k-NN retrieval
Re-ranker (stock, price, category, business rules)
Results API → web widget / mobile SDK
Events → analytics + recommendation feedback loop
- Latency target — sub-second retrieval at scale (cached indexes, GPU optional)
- Freshness — webhook on catalog update re-embeds changed SKUs
- Fallback — text search or recommendations if confidence low
Use cases by vertical
| Vertical | Why visual search wins |
|---|---|
| Fashion & apparel | Pattern, cut, and style hard to describe in keywords |
| Footwear & accessories | Match influencer / street-style photos to your line |
| Home decor & furniture | Room photos → similar chairs, lamps, rugs in catalog |
| Jewelry & watches (scoped) | Shape and metal tone similarity |
| Beauty packaging (scoped) | Find shade or product line from shelf photo |
| B2B samples (scoped) | Rep uploads client reference → closest in-stock SKU |
Platform integrations
Web storefronts
Google Lens finds the internet—we find your warehouse. Visual search trained on your angles, variants, and in-stock rules converts inspiration into orders on your domain.
Visual search vs other ecommerce AI
| Product | Focus |
|---|---|
| Visual product search | Find similar items from an uploaded image |
| AI shopping assistant | Conversational discover, compare, cart |
| Product recommendation engine | Proactive "you may also like" carousels |
| AI cart recovery | Abandoned cart win-back sequences |
| Ecommerce FAQ chatbot | Policy and post-order support |
Together: user uploads photo → visual search results → assistant answers sizing questions → recommendations on PDP.
Why Teenva AI
Vision + storefront
Ecommerce development and ML index in one teamCatalog-quality aware
We advise on image standards for better matchesIndia retail
INR filters, regional sizing context in hybrid searchOwned index
Vectors live in your cloud—not locked in a third-party marketplaceOps
Managed IT support when CDN or catalog feeds change
Delivery process
Discovery
catalog size, image quality, vertical, KPI (CTR, conversion)
Image audit
coverage per SKU, resolution, background consistency
Baseline index
embed catalog; manual QA on sample queries
UI
upload widget, mobile camera, results grid matching brand
Re-ranker rules
stock, price, category filters
Hybrid search
optional text + visual combined ranking
Pilot
limited category or traffic slice
Measure
visual vs keyword search conversion
Expand
full catalog, fine-tune, WhatsApp channel (scoped)
Explore
Frequently asked questions
One clear image per SKU minimum; multiple angles improve accuracy. We audit gaps in discovery.
Yes—upload or screenshot; optional crop helps. Results are your catalog only.
No—private index of your product media, with your stock and pricing rules.
Best for visual categories—fashion, decor, furniture; less ideal for pure commodity SKUs with identical packaging.
Apps are quick; custom fits headless, multi-brand, and fine-tuned re-ranking.
Yes—native or PWA camera capture in mobile app or mobile web.
Visual embeddings work day one—no cold-start order data required (unlike collaborative filtering alone).
Fine-tuning, better hero images, and category-scoped search improve precision; we track bad-query reports.
Query images processed for search; retention policies configurable (delete after session default).
8–10 weeks MVP (index + web widget) for catalogs up to ~100k SKUs with API/CDN access.
Related ecommerce AI solutions
Build your visual product search
Upload, camera, or drag-and-drop—similar items from your inventory in seconds on web and mobile.
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