Rules you control
Limits for refunds, transfers and price changes are explicit settings your team owns, not behaviour hidden inside a model.
RETAIL & E-COMMERCE
AI agents for retail,
from stockroom to support desk.
Retail margins depend on getting thousands of small decisions right: where stock goes, how a complaint is resolved, how a product is described. Agents can prepare those decisions at scale while your team sets the rules.
Workflows worth
handing to agents.
Each workflow names the agents involved, the point where a person decides, and what a pilot would measure.
Inventory allocation and replenishment
Today. Planners balance stock across stores, warehouses and channels with spreadsheets and changing demand signals.
- A demand agent combines recent sales, promotions and incoming orders.
- An allocation agent proposes transfers and replenishment within your service-level and cost rules.
Human checkpoint. Planners approve allocations above agreed value or risk thresholds; smaller moves can follow the rules you set.
A pilot would measure: Stock-outs on priority items · Excess stock by location · Planner time per allocation cycle
Customer service resolution
Today. Agents in the contact centre look up orders, policies and carriers before they can answer a simple question.
- A resolution agent gathers order, delivery and policy context and drafts the answer.
- An action agent prepares refunds, replacements or carrier claims within policy limits.
Human checkpoint. Refunds and exceptions above your limits go to a service lead; every action is logged against the ticket.
A pilot would measure: Time to resolution · Tickets resolved without escalation · Customer satisfaction on resolved tickets
Catalogue and pricing operations
Today. Teams write product content, fix attribute gaps and check competitor prices by hand.
- A catalogue agent fills missing attributes and drafts descriptions from supplier data.
- A pricing agent monitors agreed signals and proposes changes within your pricing rules.
Human checkpoint. Merchandisers approve price changes and publish content; nothing goes live without review.
A pilot would measure: Products with complete attributes · Time to list a new product · Price changes accepted after review
Designed for how
this industry works.
Works with your stack
Connects to your commerce platform, order management, warehouse and helpdesk tools through their APIs, scoped in discovery.
Cost that scales sensibly
High-volume steps are designed for predictable model and cloud costs, with budgets and monitoring from the first release.
Latest for
retail & e-commerce.
Updated daily by our research workflow. Papers are recent preprints; their claims are the authors’ and need evaluation.
- arXiv preprint · 26 Sept 2026Environmental Impact of Generative and Agentic AI: An in-Depth Analysis and Green Solutions
Common
questions.
Will customers talk to an AI?
Only if you choose that. Many retailers start with agents that prepare answers and actions for their service team, then automate the simplest cases once quality is proven.
Can we start with one store or one channel?
Yes, and we recommend it. A narrow pilot gives a clean comparison against current results.
What data does an allocation pilot need?
Usually recent sales, stock positions, open orders and your allocation rules. Discovery confirms what is available and how fresh it is.
Other industries: Banking & financial services · Insurance · Healthcare · Logistics, supply chain & procurement · Any other field
A GOOD PLACE TO START
Bring the ambition.
We’ll build the way forward.
Let’s talk about your project
A conversation about your goals, constraints, and next step.