Agentic Ecommerce — AI that boosts conversion, order value and customer experience
Agentic systems are transforming how e-commerce works.
With intelligent AI that understands customer intent, behaviour and needs in real time, you can deliver better search results, smarter recommendations, personalised shopping experiences, automated merchandising and faster customer journeys. Walma helps you implement agentic solutions that drive more purchases — not just more traffic.
Some clients & partners
What is Agentic Ecommerce?
A digital personal shopper — working for you 24/7
It is the next generation of AI in e-commerce. Instead of static rules or traditional recommenders, agentic systems work autonomously to optimise the customer journey. An agent can understand the customer’s context, analyse the entire product catalogue, optimise results by season, inventory, margins and customer intent, improve over time through feedback, and act in real time based on behaviour. Think of it as a digital personal shopper working around the clock to convert visitors into satisfied customers.
E-commerce agents that drive results
Each agent specialises in a part of the customer journey — together they create a seamless, AI-driven shopping experience.
AI Search & Discovery Agent
- Transforms your search function into a conversion machine
- Understands natural language ("dress for a summer wedding under SEK 1,000")
- Interprets misspellings, synonyms and context
- Returns results based on intent, not just keywords
AI Recommendations Agent
- Recommendations that actually match the customer
- Analyses session behaviour, past purchases and category intent
- Suggests complementary products based on similar customers
- Real personalisation — not just "others also bought"
Merchandising Agent
- Automated product prioritisation in real time
- Optimises by margin, stock levels and campaigns
- Adapts exposure per customer segment (B2B/B2C)
- An autopilot for merchandising that works around the clock
Agents for the entire e-commerce chain
Beyond search, recommendations and merchandising, we offer agents that handle advisory, customer service and content.
Product Advisor Agent
Answers product questions, helps the customer choose the right model or size and knows all specifications. Retrieves information from RAG and product data sheets. Reduces support load and leads to fewer returns.
Customer Service Agent
Handles order queries, returns and delivery status automatically. Connects to your systems in real time and escalates to human support when needed. Faster responses, happier customers and lower support costs.
Content Agent
Generates product descriptions, SEO-optimised copy and category pages based on your catalogue. Works directly with PIM or CMS and ensures consistent tone and quality at scale.
What sets Walma apart from other providers?
We don’t build generic AI plugins. We build agentic systems that understand your catalogue, your customers and your business goals.
Proprietary RAG technology — product-data-driven AI
Perfect for catalogues with many items. The AI gets accurate information directly from your product data sheets, PIM or CMS. No guessing, no hallucination — only correct answers based on your actual catalogue.
Agent orchestration via Ocle
We build sequential and parallel agent flows that collaborate: Search agent, Recommender agent, Pricing agent and Merchandising agent. Everything happens in real time and each agent is specialised in its task.
Integrates with all e-commerce platforms
Shopify, Centra, WooCommerce, custom headless, Medusa, Litium — we integrate with your existing platform regardless of architecture. You don’t need to switch systems to get AI-driven e-commerce.
Focus on actual business value
We measure what matters: conversion rate, average order value, time to purchase, bounce rate, search CTR and product discovery per session. Not AI for AI’s sake — but AI that drives revenue.
From analysis to AI-driven e-commerce
We start by understanding your store, your catalogue and your customers’ behaviour. Then we build agents that deliver measurable results.
Analysis & mapping
We analyse your current e-commerce journey: search behaviour, conversion data, product catalogue and technical platform. You get a clear picture of where agentic AI has the greatest impact.
Week 1Implementation & integration
We build and integrate the agents with your platform, connect product data via RAG and configure search, recommendations and merchandising. Everything is tested with your actual catalogue.
Week 2–3Optimisation & scaling
The agents go live and we optimise based on actual results. A/B testing, KPI tracking and ongoing fine-tuning ensure you get maximum return.
Week 3–4Results you can expect
Agentic AI delivers measurable improvements in the KPIs that actually drive your e-commerce forward.
+10–30% conversion rate
Agentic search and recommendations connect the right customer with the right product — faster and more accurately than traditional tools.
+15–40% average order value
Intelligent cross-sells, upsells and product advisory increase order value by matching the customer’s actual needs.
+20–50% better search precision
Fewer "no results" pages, faster product discovery and shorter customer journeys through search that understands intent, not just keywords.
Choose the plan that fits you
From an initial improved search experience to a complete agentic ecosystem for your entire e-commerce operation.
Start
- Agentic search with natural language
- Basic recommendations
- RAG connection to product data
- Dashboard with KPI tracking
Scale
- Search, recommendations, advisor and merchandising
- Integration with product feeds and PIM
- A/B testing and ongoing KPI optimisation
- Custom agent orchestration
Enterprise
- Multi-market and complex catalogue logic
- Caching strategies and margin management
- Headless integration and custom agents
- Dedicated support and SLA
Walma Agentic Ecommerce vs traditional tools
The difference between static rules and AI that understands, acts and optimises — in real time.
| Funktion | Walma Agentic Ecommerce | Traditional search/reco tools | No AI |
|---|---|---|---|
| Natural language search | Limited | — | |
| Understands customer intent and context | Limited | — | |
| Real-time personalisation per session | Limited | — | |
| Automated merchandising | — | — | |
| Agent orchestration (search + reco + pricing) | — | — | |
| RAG-driven product data (no hallucinations) | — | — | |
| Integrates with all e-commerce platforms | Limited | — | |
| AI-driven product advisory | — | — | |
| KPI focus (conversion, AOV, search CTR) | Limited | — | |
| Continuously improves with feedback | Limited | — | |
| European data sovereignty | Varies | ||
| Implementation in 2–4 weeks | Weeks–months | — | |
Frequently asked questions about Agentic Ecommerce
Yes, in most cases agentic AI replaces multiple existing systems simultaneously — and does it better. Traditional e-commerce plugins for search, recommendations and merchandising typically work in silos. With agentic systems all parts collaborate in real time. The transition happens gradually — we can start by replacing the search function and then successively take over more parts of the customer journey.
No, we have built our solution to integrate smoothly with all established e-commerce platforms. Whether you run Shopify, Centra, WooCommerce, Medusa, Litium or a custom headless solution, we have proven integration methods. Most implementations take 2–4 weeks from start to go-live.
Yes, but the impact scales with catalogue size and traffic. For smaller e-commerce businesses, agentic search and recommendations provide a noticeable improvement. But it is for businesses with large catalogues, thousands of products and high traffic that the effect truly becomes transformative.
Security and data control are built into every layer of our solution. All product data and customer interaction data is handled on European servers with encryption at every stage. Customer data is isolated per e-commerce business in separate environments.
We measure everything that matters for your e-commerce — not abstract AI quality but concrete business value. From day one we set up measurement of conversion rate, average order value (AOV), search CTR, zero-result rate, time to purchase, bounce rate and product discovery per session. We configure A/B testing for statistical significance.
Most customers see measurable improvements within the first weeks after launch. Implementation time is typically 2–4 weeks depending on catalogue size and platform complexity.