AI ordering
≈40%
Reduction in ordering time
A convenience store chain reduced ordering time by about 40% after introducing AI ordering.
Retail
Get the right products onto shelves and into customers’ hands
ActelosAI helps retail teams scope and build AI applications for replenishment, store operations and customer journeys. Start with an everyday question: is the product available, can the store respond, and will the online promise hold? Connect merchandise, inventory and store work around that decision.
01Replenish with confidence
Some products sell out while others sit in stock. What should the next order change?
02Support the storeWhat needs to reach the shelf today, and which exceptions need the manager’s attention?
03Help customers chooseOnce customers find a product, what information do they need to choose confidently?
The operating challenge
Connect the gaps between products, customers and stores
A sales change may reflect demand, a stockout, shelf presentation or campaign execution. Promotional sales need to be considered alongside discounts, waste and remaining inventory. Stock in a system still needs to be checked for availability and timely fulfilment.
Start with one specific task. Help teams understand the causes and turn recommendations into everyday store work.
AI transformation outcomes
See concrete changes, from ordering to store operations
Fresh food operations
3→1cycles per day
Fresh food markdown cycles
A major supermarket chain used AI to support fresh food clearance, reducing daily markdown cycles from three to one.
Store task management
90→30minutes
Overnight stocking shift-planning time
A major retailer used AI to support overnight stocking shift planning. Store leaders’ early estimates put planning time at 30 minutes, down from 90.
AI in everyday retail
Six everyday tasks to start from
These are application directions to design and validate together, using your retail format, business data and existing systems. The responsible teams retain decisions on products, prices, purchasing and customer commitments.
01
Demand forecasting & replenishment
Replenish for what each store really needs
Combine sales, promotions, stockout records, available stock and inbound inventory with forecasting and replenishment models. AI explains changes and flags lead-time, shelf-life and case-pack constraints, helping planners and buyers focus on exceptions that need judgment.
Data, outputs and measures
- Connected data
- Sales and promotions; stock and inbound inventory; lead times and shelf life
- Practical output
- Store replenishment recommendations, supporting rationale and exceptions
- Measures to watch
- Product availability · Write-offs as a share of sales
02
Store & frontline work
Make the next task clearer for the frontline
Receiving, shelf replenishment, price changes and customer service compete for attention. AI uses tasks, delivery and shelf feedback to prepare priorities, retrieve current procedures and summarize unfinished handovers, helping managers allocate work and follow up.
Data, outputs and measures
- Connected data
- Store tasks, delivery and shelf feedback, procedures and completion records
- Practical output
- Shift task lists, work instructions and outstanding actions
- Measures to watch
- Total task preparation and review hours · On-time completion
03
Assortment & merchandising
Shape the assortment around local customers
The same product can perform differently across stores. AI brings together sales, feedback and stockout signals, considers shelf space, price bands and product specifications, and prepares comparisons for adding, replacing or retaining products in a small-scale trial.
Data, outputs and measures
- Connected data
- Product attributes, store sales and inventory, customer feedback and shelf space
- Practical output
- Assortment differences, adjustment candidates and validation suggestions
- Measures to watch
- Category gross profit · Target demand fulfilment
04
Pricing & promotions
Understand what a promotion brings—and leaves behind
Did higher sales generate more contribution? How much inventory remains? Compare sales, discounts, costs and write-offs on a consistent basis. AI links campaign and execution records, identifies possible drivers and prepares suggestions for the next review.
Data, outputs and measures
- Connected data
- Prices and promotions, sales and costs, inventory and returns, execution records
- Practical output
- Promotion contribution review, differences to verify and adjustment suggestions
- Measures to watch
- Promotion contribution · Post-promotion inventory
05
Omnichannel orders & fulfilment
Bring the purchase promise closer to delivery
Across pickup, delivery, installation and returns, AI brings together order commitments, product availability and handover records. It flags missing items, delays and open issues, preparing follow-up suggestions and customer communication drafts.
Data, outputs and measures
- Connected data
- Orders and commitments, available inventory, pickup, delivery, installation and returns
- Practical output
- Fulfilment exceptions, follow-up suggestions and communication drafts
- Measures to watch
- On-time, in-full delivery · Exception resolution time
06
Customer understanding & shopping
Make products easier to find and choose
AI organizes permitted enquiries, reviews and purchase feedback to identify information and service gaps. Grounded in current product information, it helps explain specifications, uses and differences, preparing buying guides and comparisons for store and online teams.
Data, outputs and measures
- Connected data
- Product information, customer enquiries and feedback, permitted purchase journey records
- Practical output
- Purchase concerns, product comparisons and shopping Q&A drafts
- Measures to watch
- Target journey purchase completion · Product information accuracy
What improvement means
Measure the result—and the cost of getting there
More reliable availability
Connect sales, stock, inbound inventory and shelf life. Watch availability alongside write-offs, so extra inventory does not hide the cost of keeping products in stock.
Healthier sales
Connect assortment, promotions and purchase feedback. Look at contribution and remaining inventory together to understand which sales changes are worth sustaining.
Smoother execution
Connect tasks, handovers and completion. Track total effort, errors and customer waiting to see whether work has merely moved elsewhere.
Compare measures within the same business scope against an actual baseline. These improvement directions are not projected returns.
Related experience
Hero Market · Malaysia
Case presented in collaboration with Opxiq
Bring replenishment recommendations into store execution
An AI demand forecasting agent combines sales, inventory and store requirements to generate daily replenishment recommendations. Procurement reviews them and completes approval in the ERP. Warehouse, distribution and store receiving data feed back into planning.
Explore the caseRetail formats
A shared retail goal, different product and operating decisions
Consider stores and online channels together. Let the business problem and current conditions define the starting point.
Grocery & food retail
Start with frequent replenishment, shelf availability and promotion response. Use batch, remaining shelf-life and waste records to examine availability alongside the inventory burden.
Specialty retail
Start with sizes, colours, specifications, compatibility and buying questions. Connect assortment, assisted selling and fulfilment. For home products and durable goods, include installation and after-sales service.
Meet the experts
Bring relevant experience to a specific problem
Find the right expertise for your merchandise, operations and systems questions.
Shaun Yang
Expert Partner, Consumer Goods Industry Lead
Connect customer insight, category strategy and product innovation, using operating data to support growth decisions, commercial execution and AI adoption.
Managing Director, Gaoyan
View expert profile
Martin Qiu
Expert Partner, AI-Native Transformation & Enterprise Delivery Lead
Align retail business priorities, product direction and cross-functional delivery, turning transformation topics into coordinated team action.
Expert Partner, Gaoyan
View expert profile
Sheldon Lee
Expert Partner, Supply Chain & Operations Lead
Connect supply chain and distribution operations with commercial feasibility and regional execution conditions, clarifying the work and conditions needed for change.
Founder & CEO, Opxiq
View expert profileBefore we begin
Choose a retail workflow worth testing
Retail is the industry context; replenishment, store execution and assisted shopping are different starting points. Choose the work your team wants to improve before choosing the technology.
What is a useful first scope
Choose one store group, category or customer journey, with a named business owner. For replenishment, bring sales, available stock, inbound orders and shelf-life constraints. For store work, start with tasks and handovers. Agree how recommendations will be reviewed before purchasing or customer commitments change.
What would count as useful evidence
Agree the output and comparison period for that workflow. A replenishment trial can examine availability alongside write-offs; a store-work trial can examine preparation and review effort alongside completion. Use your own baseline rather than treating a published case result as a forecast for your stores.
Start with one store, one category or one customer journey
Tell us what you want to improve, how the team handles it today and what data could help. Together, we can define a scenario worth testing and how to tell whether it makes a difference.