The audit decides what to build and in what order. This is where it gets built, scoped to one measurable result, in weeks, not quarters. No open-ended projects, no "phase two we never reach."
One high-value use case at a time, with defined KPIs and a result you can measure. We start small on purpose: prove it works, keep it if it earns its place.
Everything here is squarely in the marketing and e-commerce lane, the work where my judgment plus AI literacy is the advantage, delivered with proven, vendor-neutral tools rather than bespoke engineering.
Every build is defined by a commercial metric before we start: conversion, order value, tickets deflected, hours returned. Never model names. If we cannot name the number it should move, we do not build it.
Single build. One contained piece of work, for example a support chatbot or a lead-qualification flow, live in a couple of weeks. The lightest way to see a real result.
Full engagement. A fixed-scope 8-week engagement that takes a priority use case from the roadmap through to a working, measured solution your team can run.
Custom model training, deep backend integration and enterprise automation are deliberately out of scope. Where a job needs heavy engineering, I say so and point you to someone who does it well.
Attributed results from published studies and other companies, what the approach is built for, not MetaGem's own results.
A peer-reviewed micro-enterprise study saw average response time drop ~46% and satisfaction rise after a modest chatbot build, the realistic-scale proof point.
SME benchmarks show well-built assistants deflecting a third to nearly half of routine tickets and cutting first-response time by 50–82%.
One e-commerce retailer reported a 9.4% revenue increase after adding AI personalization, the kind of lever a scoped first build targets.
An honest filter is cheaper for both of us than a wasted first meeting.
Seventeen years of marketing and e-commerce work, and daily production use of these tools. The person building understands the process being automated, which is where most technically correct but useless work comes from.
Everything is built on proven platforms in your own environment, and handed over documented. No licence you have to keep paying me for, and no system only I can maintain.
What is not on offer: guaranteed savings, an open-ended project, and a build that quietly never reaches production.
A real client example belongs here: the problem, what was built, and what it moved. Left empty on purpose rather than filled with an invented story.
By value against feasibility, usually from an audit or workshop that already ranked them. Without one, the first conversation does a rough ranking: building the second-best thing well is worse than building the best thing adequately.
Weeks, not quarters, scope fixed before the start. If something cannot be delivered in that window, you hear it at scoping, not at the deadline.
A defined handover: documentation, a recorded walkthrough, training, a named owner on your side, and an agreed support period. Ongoing operation is available, never a condition.
No. This is configuring and orchestrating proven platforms, which is what makes weeks and sensible cost possible. Custom model training and deep backend engineering get referred out.
You do. It runs in your environment, on your accounts, with your data, and the documentation is written so somebody other than me can maintain it.
The fastest way to a useful build is to start from the audit, so we build what actually matters first. Request a call and we will map it.
Request a callFixed scope · one measurable result · no lock-in
