AI for retail that converts and retains
Catalog enrichment, support deflection and merchandising copilots — connected to your POS, OMS and storefront so they move revenue, not just demos.
Where AI actually moves the needle in Retail & E-commerce
Retail AI lives or dies on the catalog and the customer conversation. A thin product description with no attributes kills both search and conversion; enriching titles, attributes and copy at scale — accurately, in your brand voice and across languages for India and the World — is unglamorous work that directly lifts discoverability and sales.
Support is the highest-volume, highest-cost surface. A well-grounded support agent that knows your order status, return policy and product details can deflect the repetitive WISMO and returns questions while escalating the genuinely tricky ones with full context. The win isn’t replacing agents — it’s letting them spend time where empathy and judgment actually matter.
Behind the storefront, merchandisers and ops teams want copilots: surface slow-movers, recommend reorders, draft promotions, and answer ‘why did this SKU spike’ in plain language over your sales data. We integrate with POS, OMS, Shopify and your data warehouse so these tools act on live commerce data, not a stale export.
What we build for Retail & E-commerce teams
Catalog enrichment engine
Generates accurate titles, attributes and descriptions in your brand voice across languages to lift search and conversion.
Support deflection agent
Resolves WISMO, returns and product questions grounded in live order and policy data, escalating the hard cases with context.
Merchandising copilot
Answers sales-data questions in plain language and surfaces slow-movers, reorder needs and promo ideas for the merchandiser.
On-site shopping assistant
A conversational product finder that turns vague intent into the right SKU and increases basket size.
Review & sentiment digest
Clusters reviews and tickets into ranked product and CX issues for the category team to act on.
Returns-reason analyzer
Classifies return reasons to expose sizing, quality and listing problems before they spread across the catalog.
How we deliver
| Capability Parameter | System Specification |
|---|---|
| Integrations | POS, OMS, Shopify/Magento/WooCommerce, payment gateways, data warehouse, helpdesk |
| Models | Frontier LLMs for copy and conversation; tuned models for attribute extraction and sentiment |
| Guardrails | Brand-voice constraints, factual grounding on live catalog/order data, escalation on low confidence |
| Engagement | Fixed-scope build, 4–10 weeks, then optional operate retainer |
| Typical budget | ₹20L–₹50L / $20k–$60k per production system |
| Data & compliance | Customer-PII protection, PCI-aware boundaries around payment data, per-store isolation |