- Industry
- Retail and F&B
- Channels
- Web · WhatsApp · POS / e-commerce
- Deploys
- Cloud, hybrid or on-premise
- Control
- Human approval where it matters
- Pilot
- Measured proof in 4 weeks
- Built on
- Agent in a Box
Solutions/Retail and F&B/Retail AI Agent
IND-07Agent 01 of 04
Retail AI Agent
Knows what each customer wants, predicts what the shelf needs and answers every question — instantly.
25–35%Less overstock & stockouts
80%Queries resolved without a human
01 — The challenge today
Where the
time goes.
- Generic experiences drive low conversion and basket abandonment.
- Demand-forecasting errors leave shelves empty or overstocked.
- Customer queries pile up in contact-centre queues.
- Pricing decisions lag behind competitor moves.
02 — How the agent works
It acts —
not just answers.
Every step runs inside your systems and under your rules — with a person approving anything that matters.
Analyses browsing and purchase signals to surface hyper-relevant recommendations.
Forecasts SKU-level demand using seasonality, promotions and external signals.
Handles product, order and returns queries 24/7 across all channels.
Adjusts prices dynamically based on demand, margins and competitor data.
03 — Business value
What it
pays back.
Outcomes your team can measure — not a demo that never leaves the lab.
Outcome 01
Bigger baskets
personalisation lifts average order value.
Outcome 02
Leaner inventory
25–35% reduction in overstock and stockouts.
Outcome 03
Always-on CX
80% of queries resolved without a human agent.
Outcome 04
Margin protection
real-time pricing keeps you competitive.
A retail engine that personalises, predicts and serves — across every channel, every hour.
04 — Getting started
Proof in
four weeks.
We would rather prove one use case properly than describe five. Pick the process that hurts most — we will run it on your own data in four weeks.
Week 1 · Scope
One process, one team, one measure. Agree what “better” means — in hours, days or cost — and measure it before anything changes.
Weeks 2–3 · Shadow
The agent runs alongside your team on live work, with a person approving each action. Its output is compared honestly with what your team produced anyway.
Week 4 · Measure
Report against the baseline, agree the guardrails that stay and document what your team owns. Then decide whether the next process follows.
Three operating principles
Principle 01
Acts inside your systems
Works where the work already is — your core systems, documents, inboxes and channels. No new tool for your team to copy things into.
Principle 02
Bounded by your rules
Limits are set per process: what the agent may do on its own, what needs human approval and what it may never do. Anything outside the boundary goes to a person.
Principle 03
Reviewable and reversible
Every step is logged — what it read, what it changed, who was notified and when. Evidence you can use in audit and compliance reviews.
05 — FAQ
Questions,
answered.
The short answers buyers ask us most about the Retail AI Agent.
What does the Retail AI Agent do?
Knows what each customer wants, predicts what the shelf needs and answers every question — instantly. Analyses browsing and purchase signals to surface hyper-relevant recommendations. Forecasts SKU-level demand using seasonality, promotions and external signals.
Which problems does it solve for Retail and F&B teams?
Generic experiences drive low conversion and basket abandonment. Demand-forecasting errors leave shelves empty or overstocked. Customer queries pile up in contact-centre queues. Pricing decisions lag behind competitor moves.
What business value can we expect?
Bigger baskets: personalisation lifts average order value. Leaner inventory: 25–35% reduction in overstock and stockouts. Always-on CX: 80% of queries resolved without a human agent. Margin protection: real-time pricing keeps you competitive.
Does a person stay in control?
Yes. The agent works within limits you set for each process: what it may do on its own, what needs human approval and what it may never do. Every action is logged, reviewable and reversible.
How quickly can it be deployed, and where does it run?
Most teams start with a four-week pilot: scope one process in week 1, run the agent alongside your team with human approval in weeks 2–3, and measure the results against the baseline in week 4. It works across Web · WhatsApp · POS / e-commerce, and can be deployed in the cloud, hybrid or fully on-premise.
06 — Explore
More for Retail and F&B.
Every agent can be combined, adapted or built from scratch around the way your business runs. See all 29 solutions →
Retail AI AgentKnows what each customer wants, predicts what the shelf needs and answers every question — instantly.
Agentic F&B SolutionTakes orders and reservations on WhatsApp, keeps the kitchen stocked and answers every guest — so your team can focus on the food and the floor.
Appointment Booking Web AgentTurns website visitors into booked appointments — qualifying the enquiry and dropping the slot straight into your calendar, day or night.
Appointment Booking Voice AgentAnswers the phone in your brand's voice and books, moves or cancels appointments in the live calendar — on the first ring.
Your move
Specify
your agent.
Tell us the process that hurts most. We'll have an agent working on it within weeks.
Book a demo