Advisory and implementation
Agentic commerce: a practical playbook
AI agents are reshaping how e-commerce operates, from product discovery to order fulfilment. This is what agentic commerce means in practice for retailers and brands, where it creates value, and how we help you capture it.
Definition
What agentic commerce actually is
Agentic commerce is e-commerce where AI agents — software that perceives context, reasons across data sources and acts autonomously — handle tasks across the commercial stack without constant human intervention.
Unlike basic automation or chatbots, agentic systems chain multiple steps together. A catalogue and product agent continuously enriches and optimises your product data. A commerce agent personalises journeys and handles transactional interactions for both human shoppers and AI buyers. A CRO and experimentation agent runs and scales winning experiences across the funnel.
The practical result is an operating model where AI handles the repetitive, rules-based, high-volume decisions — freeing your team for strategy, creative direction and the exceptions that genuinely need human judgement.
Where the return is
Five use cases delivering measurable ROI today
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Smart search and discovery
An agent monitors search queries and browsing patterns, dynamically re-ranks results and surfaces relevant products — lifting conversion without manual merchandising.
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Autonomous replenishment
An agent tracks inventory levels, supplier lead times and sales velocity in real time. When stock dips below threshold it generates and submits purchase orders automatically.
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Personalised promotions
Instead of blanket discounts, an agent analyses customer lifetime value, basket composition and timing signals to deliver individual offers at the right moment.
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Post-purchase handling
An agent handles order tracking queries, initiates returns, coordinates with carriers and sends proactive delivery updates — reducing support ticket volumes by up to 40%.
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Dynamic pricing
An agent continuously monitors competitor pricing, demand elasticity and margin targets, adjusting prices within set guardrails to maximise revenue.
Architecture
A layered capability stack, not a product
At the foundation sits your existing commerce infrastructure — catalogue, pricing engine, inventory, fulfilment. Above it, agents operate as autonomous decision-makers connected through APIs and empowered to act.
- Data and context layer
- Real-time product data, customer profiles, session context and inventory signals feed the agents the information they need to act.
- Agent reasoning layer
- LLM-powered agents interpret intent, plan multi-step actions and execute decisions — from product recommendation through to checkout completion.
- Integration and orchestration layer
- Agents connect to your commerce platform, ERP, CRM and logistics systems through secure API integrations, acting as the nervous system of the operation.
Engagement models
Three ways to start
We work with brands at different stages of the journey. Each model has a defined scope and a defined end point.
- 4 weeks
Agentic readiness assessment
A structured diagnostic that maps your current tech stack, identifies agentic opportunities and delivers a prioritised roadmap. Built for brands considering their first AI-powered initiatives.
- 8–12 weeks
Agent design and implementation sprint
A hands-on engagement to design, build and deploy your first agentic use case — from scoping through to live launch with measurable KPIs.
- Ongoing
Strategic advisory retainer
Support for teams scaling their agentic capabilities: monthly sessions, vendor evaluation, architecture review and access to our practitioner network across Europe.
Next step
Ready to explore agentic commerce?
Whether you are starting to explore AI agents or ready to deploy at scale, we can help you move faster and with fewer wrong turns.