AI API for e-commerce in India

E-commerce in India thrives on personalization and trust. With rising competition and thin margins, AI-powered product discovery, dynamic pricing, and instant support are table-stakes. unoblox's OpenAI-compatible API lets you embed state-of-the-art reasoning and language understanding into your e-commerce stack, billed in rupees.

Product recommendation engine

Recommendations drive 30%+ of e-commerce revenue. Build a semantic search and ranking system using unoblox embeddings (Qwen3 embedding at ₹0 on freemium tier) to find the right products, then Qwen3 235B (₹9.11 / ₹55.67) to rank and explain why a product matches a user's query in natural language. Reranking at ₹0 ensures your fastest SKUs bubble to the top.

Dynamic pricing & inventory

Use Claude Sonnet (₹202.46 / ₹1,012.28) to analyze competitor pricing, seasonal demand, and inventory levels in one step. Feed it your cost structure and target margin; it returns a pricing recommendation + confidence. Run this hourly across your catalog without breaking the bank.

Review summarization & moderation

Thousands of customer reviews every week. DeepSeek V3.2 (₹26.32 / ₹38.47) quickly summarizes sentiment, extracts pros/cons, and flags spam or harmful content. Show potential buyers the top 3–5 authentic insights per product instead of a raw review feed.

Use-case	Recommended model	₹ input/output	Why
Semantic search/rank	Qwen3 + Reranker	₹0 (freemium)	Free, native pipeline
Pricing logic	Claude Sonnet	₹202.46 / ₹1,012.28	Multi-factor reasoning
Review analysis	DeepSeek V3.2	₹26.32 / ₹38.47	Speed + accuracy
Multi-language chat	Qwen3.8-27B	₹0 / ₹0	Hindi, Tamil, regional

Frequently asked questions

How do I avoid low-quality AI-generated product descriptions? Use an open-weight model like Qwen3.8-27B for drafts, then review+edit. Reserve Claude Opus (₹506.14 / ₹2,530.71) for premium brand writing; cost per SKU is low if you're selective.

Can embeddings catch counterfeit products in search? Yes. Train a classifier on known counterfeits; embeddings isolate fraud signals. Combine with Qwen3's reasoning for a two-stage fraud filter.

What if my catalog is in Hindi or other Indian languages? Qwen3.8-27B natively understands Hindi, Tamil, Telugu, Kannada. No translation needed; faster + cheaper than English-first pipelines.

Do I need to host models myself? No. unoblox is fully managed. Scale from 1 request/day to 1M; pricing is per-token, not per-seat or per-deployment.

Can I use embeddings for user profile tagging? Yes. Build user interest profiles from browsing/purchase history via embeddings, then personalize product feeds and search results dynamically.

Is there a free tier to test? Yes. Qwen3.8-27B is completely free (₹0), and embeddings/reranking are freemium. Test on real e-commerce data before scaling.

Get started in rupees → https://unoblox.ai/sign-in