AI Retail Assistants That Convert — Grounded in Catalog and Stock
Hilal and TwinFusion deployed conversational AI across web and messaging channels — RAG over product catalogs, promotion rules, and live inventory with human escalation when confidence drops.
The challenges
Domain problems in retail & commerce that block production outcomes.
01
Generic chatbots erode trust
Shoppers get wrong product info, invented promotions, and no path to a human when it matters.
02
Inventory hallucination risk
Recommending out-of-stock items damages conversion and increases returns.
03
Channel fragmentation
Web chat, WhatsApp, and in-app support need one knowledge layer — not three bots.
Our capabilities
Concrete building blocks for this domain — engineered for production, not demos.
Catalog RAG
Chunked embeddings with metadata filters for category, region, and sensitivity.
Live inventory tools
Stock checks and reservation logic before recommendations ship.
Basket recommendations
Cross-sell flows tied to promotions and availability.
Omnichannel delivery
Web, WhatsApp, and in-app from one orchestration layer.
Confidence scoring
Automatic human handoff with conversation history intact.
Evaluation pipeline
Regression tests when products, policies, or models change.
Assistants that know the catalog — and when to hand off.
Hilal and TwinFusion deployed grounded retail AI across product Q&A and recommendations. Answers stay tied to live inventory and policy, with human escalation when confidence drops.
Read the assistant engagementWe have the best approach
A proven path from discovery to an operated system — so teams own outcomes in production, not just a handoff deck.
Ingest catalog, policies, and FAQs with permission-aware retrieval.
Inventory, orders, and CRM connectors with audit logging.
Launch on highest-volume channel with human-in-the-loop review.
Track deflection, conversion lift, and expand channels.
How Aqeeq serves retail & commerce
Practical answers about how we engage, integrate, and operate in this domain.
We ground answers in catalog RAG, live inventory tool calls, evaluation suites, and human escalation — treating retrieval and tools as production systems, not a chatbot demo.
Yes. One orchestration layer serves web, WhatsApp, and in-app channels so knowledge, inventory checks, and escalation rules stay consistent.
Recommendations and availability answers go through audited tool calls into live stock systems before they reach the shopper.
Want a retail assistant that converts without hallucinating stock?
Bring a sample catalog and support volume — we will show where RAG, tools, and escalation belong in your stack.