AI for Retail
A customer messages "Do you have this in size M?" at 9 PM. Nobody answers until morning. By then, they have already bought from a competitor who responded in 30 seconds. Multiply that by a dozen messages a day and you are leaking revenue through a problem that has a straightforward engineering fix.
An AI retail agent costs less than a part-time hire, runs 24/7, and pays for itself in weeks.
The Problem
- Stockouts surprise you. You find out a product is gone when a customer complains, not before
- Slow responses lose sales. Customers message asking about availability and wait hours for a reply. They do not wait.
- Manual inventory tracking breaks at scale. Spreadsheets and back-of-house checks lag behind reality
- Multi-channel coverage is impossible manually. Website chat, Instagram, WhatsApp, and SMS all need answers simultaneously
Why Now?
The unit economics finally work. An AI retail agent costs less than a part-time hire, runs 24/7 with built-in failover and graceful degradation, and pays for itself in weeks.
- Instant answers are expected. Shoppers compare across tabs and buy from whoever responds first
- Multi-channel demand is standard. Your customers are already messaging you on four platforms. They expect answers on all of them
- Guardrails are mature. The system only reports real inventory data - it never fabricates availability or pricing
What I Build for Retail
Retail AI with guardrails: only real inventory data, never fabricates, and escalates gracefully when a question falls outside its scope.
- Real-time stock checks. Connected to your inventory system, answers reflect what is actually on the shelf right now
- Order status updates. Customers check shipping and delivery without waiting for a human
- Low-stock alerts. Proactive notifications when popular items are running low so you can reorder before stockouts
- Product recommendations. Suggest alternatives when an item is out of stock, or complementary products to increase basket size
Every response is grounded in your actual data. The bot never invents a product, fabricates a price, or promises availability it cannot confirm. This is the same guardrail-first approach I apply across every system I build - the Arepa.AI platform uses the same architecture for multi-channel customer communication, and the principles transfer directly to retail.
The Process
- Strategy Session. We assess your inventory system, customer channels, catalog size, and current response times.
- System Design (Week 1-2). I design the integration architecture, channel coverage, and escalation rules.
- Build & Integration (Week 3-5). I build the bot and connect it to your inventory system, order management, and messaging channels.
- Launch & Training (Week 6). Your team learns to manage escalations and monitor the system. I watch the first two weeks of live traffic.
- Optimization (Monthly). Review response accuracy, sales impact, and customer satisfaction.
Investment Context
| Scenario | Impact | |---|---| | 5 unanswered messages/day, 20% would have converted | 1 lost sale/day | | Part-time staff for customer messaging | $20,000-35,000/yr | | AI retail agent | Less than a part-time hire, 24/7 coverage |
The system is not replacing your team. It handles the repetitive volume - stock checks, order status, basic questions - so your staff can focus on the interactions that require a human: complex returns, VIP customers, and in-store experience.
Let's scope your retail system
Book a $300 strategy session where we assess your inventory system, customer channels, and catalog size, then design a bot scoped to your store. Fully credited if we proceed.
- 60-minute focused session
- Actionable next steps document
- Fully credited toward projects
Ready to stop losing sales?
Use the form below to describe your current setup and I will respond within one business day with a tailored proposal.