Platform · Infrastructure
The right experience for every visitor, without code changes.
The thesis
Serving the same site to every visitor is leaving money on the table. Running experiments by hand is too slow to catch up. The Personalisation & Experimentation Engine collapses both into one substrate, so agents can target, test, and learn at a cadence no human team can match.
What it does
Each capability is wired into the same data model and shared by every agent. Nothing here is a side feature; the platform is the product.
Segment by source, geo, device, behaviour, lifecycle stage, predicted value. Composable rules, no engineering tickets.
Built-in statistical guardrails, auto traffic allocation, auto winner calls, auto archive. Experiments graduate themselves.
Creative Agent generates variants natively. The engine deploys, measures, and rotates them without an operator in the loop.
Headlines, hero imagery, recommendations, pricing, promos. Anything on the page is targetable, no code changes required.
Experiments never stop. As one ends, the agent spins up the next, building a stack of compounding wins.
Every architectural decision here reflects a strong opinion about what makes AI useful inside a real growth team, not what makes a demo land.
Belief 01
Most experimentation tools assume an engineer ships the change. We assume an agent does. That single shift is what makes experiment-per-week velocity possible.
Belief 02
Rule-based personalisation rots the moment the catalogue or audience moves. Agent-driven personalisation re-tunes itself as the data shifts.
Belief 03
Calling a winner on noise is worse than not testing at all. The engine refuses to graduate variants until the math is honest.
How the agents use it
Personalisation & Experimentation Engine is shared infrastructure. Every agent reads from it, so the work each one ships is consistent with everything else moving through the store.
CRO Agent
Designs, deploys, and retires experiments end-to-end without an operator.
Creative Agent
Variant generation feeds directly into live experiments, no hand-off.
Merchandising Agent
Collection ordering and product cards personalise per visitor segment.
Analytics Agent
Reads experiment outcomes and writes them back into Brand Context.
In one line
Most brands run two or three meaningful experiments a quarter. With this engine, the floor is two or three a week.
How the platform behaves
Agents read from structured, retrievable context. Prompts can lie about what an AI knows. A graph cannot.
Every agent queries the same data layer. No copies, no divergence, no silent disagreements between tools.
The platform tunes itself as the catalogue, audience, and market move. Static defaults rot fast.
Every action ties back to the context it read and the data it saw. Nothing the agents do is a black box.
The rest of the platform
Brand Context Engine
Your brand's memory, always at hand for every agent.
Unified Data Platform
Shopify, Meta, Google, Klaviyo and clickstream, tied to every customer.
Inspiration Libraries
Curated creative and merchandising references your agents draw from.
Playbooks
Battle-tested growth workflows, automated end to end.
A 20-minute walk-through. Real catalog, real data, the platform running against a duplicate of your live store.
Join the Waitlist