Turning customer signals into margin with applied AI
Retail runs on margin and velocity. We build AI that turns first-party behavior, inventory, and content into owned systems — personalizing the storefront, sharpening merchandising, and defending margin from demand forecast to fulfillment.
Why AI mattersin Retail / E-commerce.
In retail, margin and velocity decide everything. AI matters when it turns first-party signals into real contribution-margin gains — from demand forecast through to fulfillment.
Our point of view is values-focused and ROI-first: every initiative ties to margin, we amplify your merchandising and marketing teams rather than replace them, and we build owned systems you control instead of black boxes.
- 01Margin is thinEvery point of contribution margin matters.
- 02Velocity decidesForecast and personalize in real time or lose the sale.
- 03First-party data winsYour behavioral data is the unfair advantage.
- 04Experience is everythingPersonalized beats generic, every time.
How we workin Retail / E-commerce.
One method, tuned to your context: we design the whole system — people and AI — rank every move by ROI across four lenses, and build in iterative cycles that compound value.
Design the whole system
We map the journey from demand forecast to fulfillment, designing where AI personalizes and optimizes and where merchandising and marketing teams stay in control — with adoption built in.
Quantify the value
We score every opportunity across four lenses tied to the P&L — contribution margin, velocity, conversion, and risk — so we build what defends margin, not vanity metrics.
Tailor to your context
We build owned systems on your first-party data, integrating with your storefront, inventory, and martech — tuned to your catalog and customers, not a black box.
Iterate and compound
We ship a first capability fast, measure against margin and sell-through, and iterate each cycle — compounding velocity and contribution margin.
The AI opportunityin Retail / E-commerce.
fewer stockouts and markdowns
first-party data activated
target ROI within 90 days
Photo: Pexels
Purpose-built applicationsfor Retail / E-commerce.
Personalized Storefront Engine
Imagine every shopper seeing a store merchandised for them — products, content, and offers ranked in real time by intent, not last week's batch job.
CRFT builds the real-time personalization and ranking layer over your catalog.
Demand & Inventory Forecasting
An AI model reads sell-through, seasonality, and signal noise to call demand by SKU and location — cutting stockouts and markdowns before they hit the P&L.
CRFT engineers the forecasting pipeline and replenishment signals.
AI Merchandising Diagnostic
Know exactly where AI moves the needle across discovery, pricing, and lifecycle — a structured assessment that ranks use cases by margin impact and effort.
SPRK delivers the prioritized, ROI-ranked merchandising roadmap.
Contribution-Margin ROI Tracker
See which AI-driven campaigns, recommendations, and pricing moves actually defend contribution margin — live dashboards your finance team trusts.
KNTRL ties AI-driven commerce spend to contribution-margin outcomes.
Sourcing Feels Faster. Is It Actually Working?
Your team says AI is helping. Sourcing feels faster. The analysts are more efficient. But when your LP asks what it's actually producing, you don't have a number you trust. That gap — between AI activity and AI value — is where most PE firms are stuck right now. Operational ROI is the first place to close it: not by chasing more AI activity, but by mapping the workflow, setting a real baseline, and proving that time saved actually became value created.
Pablo Cruz Pou · August 17, 2026 · 17 min read
The Accountability Gap: What Private Equity Gets Wrong About Measuring AI
A four-lens framework for capturing the full spectrum of AI value — and risk — across every dimension that matters to PE sponsors, operators, and boards.
Pablo Cruz Pou & Fritz Desir · May 30, 2026 · 17 min read
The Agentic Enterprise: A Field Report
What we learned putting AI agents into real operations — where they earned their keep, and where they quietly fell over.
Fritz Desir · May 28, 2026 · 3 min readRetail / E-commerce,answered.
Mostly your first-party signals — behavior, catalog, and inventory data. We build the personalization and forecasting layer on top of the commerce data you already collect.