An AI-powered shopping assistant designed, built, and shipped ahead of peak season — model-agnostic, observable, and ready for production traffic.
A growing retail brand wanted an AI-powered shopping assistant live before peak season — not in six months, not after a lengthy vendor RFP, but in weeks. Shoppers needed contextual product recommendations, sizing guidance, and order-status answers without leaving the purchase flow. The internal team had strong merchandising instincts but no production AI experience, and leadership was wary of locking into a single model provider that might be obsolete by next quarter.
The experience had to feel native to the existing storefront, handle real catalog and inventory data accurately, and ship with enough observability that the team could tune prompts and measure impact from day one.
Froxfire scoped a four-week delivery sprint focused on a model-agnostic AI gateway, retrieval-augmented generation over the product catalogue, and a lightweight web embed that matched the brand's design system. We indexed product descriptions, FAQs, and policy documents into a vector store, wired an AI gateway that could route to multiple LLM providers, and built guardrails for tone, hallucination risk, and escalation to human support.
Full observability — latency, token usage, conversation outcomes, and conversion attribution — was built in from the start so merchandising could iterate without engineering bottlenecks. We ran load tests against projected peak traffic and handed over runbooks before go-live.
The assistant launched in four weeks, ahead of the seasonal deadline. Conversion among shoppers who engaged with the assistant rose 9% compared to the prior baseline. The client was satisfied enough to return for two additional AI projects — expanding personalization and post-purchase support automation.
Product and engineering teams now treat AI as a repeatable capability rather than a one-off experiment, with clear metrics tying assistant interactions to revenue outcomes.
The solution combines an AI gateway for provider flexibility, RAG over structured and unstructured catalogue data, a web-based conversational UI embedded in the storefront, and end-to-end observability for prompts, latency, and business KPIs. Infrastructure scales horizontally for peak events without re-architecting.
Let's ship a production-ready experience on your timeline.