Forward deployed engineers for e-commerce and marketplace ops. Pricing, marketplace offboarding, CX, paid media, CDP — built, shipped, and operated. See the proof →
This is one capability within our forward deployed model. See our live engagements →
E-Commerce

We deployed AI at a UK fashion retailer. It delivered £6.4M. We're still there.

E-commerce — and the marketplace operations that sit underneath it — is the only thing we do. Forward deployed engineers embedded in your business, building AI agents for pricing, Mirakl marketplace offboarding, sale-launch QA, customer data, CX, and paid media. Then we stay and run them. Every initiative tracked against EBITDA. Success-based pricing so our incentives match yours.

What We've Actually Done in E-Commerce

At a major UK fashion e-commerce retailer processing 2 million requests per day with 16.4 million customer profiles — we deployed a full AI operations programme across 119 EBITDA-tracked initiatives. This isn't a theoretical capability page. These are real systems we built, deployed, and still run.

The AI pricing engine replaced a £75K/year vendor and delivered +77% revenue uplift in five weeks. The customer data platform replaced a £45K/year CDP vendor and identified £8.3M in margin protection through discount suppression. Cloud hosting dropped 60% — from £38K to £15K per month — by moving workloads off AWS to dedicated infrastructure. £6.4M in annualized value creation, every pound tracked to a P&L line.

E-commerce is where we have the deepest proof. The problems are familiar: margin erosion from over-discounting, expensive SaaS vendors with overlapping functionality, cloud bills growing unchecked, and manual processes that AI handles better. We know how to fix these because we've done it.

What We Deploy for E-Commerce

Four core capabilities. Each one we've built and operated in production. We don't advise on these — we deploy them and stay to run them.

01

AI Pricing Optimization

In-house AI pricing engine that replaces expensive vendors. Elasticity modelling across your full catalog, weekly automated markdowns, daily consignment pricing, real-time monitoring every 15 minutes. We built this for a UK fashion retailer. It delivered +77% revenue uplift in five weeks and eliminated a £75K/year vendor.

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02

AI Agent Deployment

Purpose-built AI agents for pricing, CX, marketplace operations, DevOps, and CRM. Each replaces manual processes — product description generation, first-line customer queries, real-time site monitoring, automated reporting. We deploy them, train them on your data, and operate them ongoing.

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03

Customer Data Platforms

We replaced a client's £45K/year CDP vendor with an in-house build on Snowflake. RFM scoring, churn prediction, intelligent segmentation across 16.4 million profiles. Discount suppression alone identified £8.3M in margin protection. The in-house build outperforms the vendor because it trains on your data, not industry averages.

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04

Cloud & Infrastructure

Most e-commerce businesses overpay for cloud by 50–80%. We took one retailer from £38K/month to £15K/month by moving workloads off AWS to dedicated infrastructure. Zero downtime, CDC pipelines for data consistency. £276K/year back on the P&L. We audit, migrate, and manage ongoing.

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£6.4M
Annualized Value Creation
At a single UK fashion e-commerce retailer
+77%
Revenue Uplift
AI pricing engine, five weeks after deployment
119
EBITDA-Tracked Initiatives
Every one tracked, owned, and board-reported
60%
Cloud Cost Reduction
£38K to £15K/month — £276K/year saved

How We Work

Discovery call. You tell us where it hurts. We identify the easy wins together — report automation, disconnected systems, KPI dashboards, pricing analytics, content growth plans. We start with impactful, quick projects and deliver results within two weeks. No six-month roadmaps. No death-by-committee.

We don't leave. We keep the agents running, we're on hand 24/7 via a dedicated Slack Connect channel, and we keep finding new margin. As we roll out AI across departments, we educate your team on the benefits. We're sensitive to the impact on staff — this isn't about cutting heads, it's about making everyone more efficient. The agents get smarter. Your margins keep improving.

Frequently Asked Questions

How does AI pricing optimization work for e-commerce?

We build an in-house AI pricing engine trained on your transaction data. It calculates price elasticity at the category level — understanding that a 10% markdown drives 40% more demand in one category but only 5% in another. It generates weekly markdown recommendations across your catalog, with real-time monitoring every 15 minutes to catch demand shifts, discount code conflicts, and margin floor breaches. At one UK fashion retailer, this delivered +77% revenue uplift in five weeks.

What results have you delivered for e-commerce businesses?

At a major UK fashion e-commerce retailer, we delivered £6.4M in annualized value creation across 119 tracked initiatives. The AI pricing engine delivered +77% revenue uplift in five weeks. Cloud hosting costs dropped 60%. The customer data platform identified £8.3M in potential margin protection through discount suppression. These are real numbers from one engagement — our strongest vertical.

Can you replace our existing SaaS vendors with in-house AI?

Yes — we've done it. At one e-commerce client we replaced a £75K/year pricing vendor, a £45K/year CDP vendor, and multiple monitoring and analytics tools with in-house systems built on their data. The in-house builds outperformed the vendors because they train on your specific customer behaviour rather than industry averages. Zero ongoing licence costs after deployment.

How does your pricing work?

Base retainer plus performance fee tied to measurable margin improvement. We align our economics with yours — if we don't deliver EBITDA impact, we don't earn the performance component. Every initiative is tracked against actuals with monthly reconciliation.

What size of e-commerce business do you work with?

E-commerce businesses generating £20M+ in annual revenue. You need sufficient transaction data to build meaningful AI models and enough operational complexity that AI agents create real leverage. Our flagship e-commerce engagement involved 2 million requests per day and 16.4 million customer profiles.

See the proof, then talk.

Read our fashion e-commerce case study first. If it resonates, book a call. We'll review your P&L, tech stack, and operations to identify where AI can permanently improve your margin.