AI in your operations — not bolted on. Built in.
Execution Space helps e-commerce and DTC brands make AI part of how the business runs: data warehouses and connectors, AI reporting agents, automation that retires spreadsheet ops, and the change management that makes it stick. Restructured AI-forward in 2023 — every solution we ship is built that way.
Four stages, in order.
Assess
Where AI actually fits your operations — and where it doesn't. Tool sprawl, data fragmentation, a manual-process inventory, and honest team readiness.
Roadmap
The build order, the buy-vs-build calls — yes, including "do we need an ERP, or a warehouse plus connectors and agents" — and the cost logic behind each.
Build
Connectors into Shopify, Amazon, Meta, and Google; a queryable warehouse; AI reporting agents your team actually asks questions of; automations that remove the copy-paste layer.
Enable
Adoption is a change-management problem, not a tooling problem. Training, working agreements, and an operating rhythm so the tools get used after the novelty wears off.
The seat nobody advertises for.
A lot of companies have one person — often self-taught, often brilliant — building AI tooling faster than the organization can absorb it. What they need isn't a junior developer. It's an operator who speaks both languages: the build and the business. That's the seat we take.
AI-forward operations — common questions.
What does "AI-forward" mean?
AI-forward means AI is part of how the business runs rather than a tool bolted onto the side of it. In practice: the data is connected and queryable, reporting and analysis happen without someone rebuilding a spreadsheet, and the team has working agreements for where AI is used and where it isn't. We restructured AI-forward in 2023 and build every solution that way.
Do we need an ERP, or can AI reporting replace one?
They solve different problems, so the honest answer is that it depends on what's actually breaking. An ERP is a system of record — it enforces process around inventory, orders, and finance. AI reporting on a warehouse plus connectors is a system of insight — it answers questions across tools you already run. If your pain is fragmented reporting and manual roll-ups, the warehouse route is faster and far cheaper. If your pain is process control and no single source of truth for transactions, reporting on top of the mess won't fix it. We make that call with you before anything gets bought.
What AI tools do you work with?
Claude, plus the stack that makes it useful: a queryable data warehouse, connectors into the platforms you already sell and market on, and agents built against your own data. The model matters less than the plumbing and the adoption around it.
How do you handle adoption and change management?
Adoption is a change-management problem, not a tooling problem. We build training, working agreements, and an operating rhythm into the engagement so the tools still get used after the novelty wears off — and we measure whether they are.
What does an engagement look like?
Four stages: assess where AI actually fits, roadmap the build order and the buy-vs-build calls, build the connectors and warehouse and agents, then enable the team so it sticks. Engagements can start at any stage, but we don't skip the assessment.
Not sure whether this is the work you need?
Email contact@executionspace.com and we’ll set up a time — twenty minutes, no deck.
Or start a project →