AI for retail, built for the 5–100 person shop.
Physical, online, and omnichannel operators: businesses where the margin lives in 1,000 small operational calls a week, most of them made by hand.
Where does AI actually pay in retail?
Three places, in our experience. These are the clearest wins we see in shops like yours, not results we promise. In every one, the machine does the counting and the watching; the merchant keeps the call on what goes on the shelf.
What the system says matches what is on the shelf.
Counts drift, channels disagree, and reorders get made on gut and memory. An automation reconciles stock across your channels and drafts the reorder before the gap becomes a stockout. You still decide what to buy.
The routine ticket answered fast, the hard one routed to a person.
Most of the queue is where-is-my-order, returns, and sizing. An agent drafts those replies from your real order data and escalates the angry, the odd, and the high-value to a human who can actually fix it.
Merchandising decisions start from a draft, not a blank sheet.
An agent assembles what is moving, what is stuck, and what last season says about next month, so the buying decision starts with the evidence on the table. The merchant still makes the call. We wrote about how the pattern-finding works, and where it stops, in The Prediction Engine.
For most retail operators the right first move is the AI Readiness Audit: two to four weeks mapping where the hours and the margin actually go before anyone builds anything. If a $25-a-month subscription might cover it, that question is answered squarely here. Pricing is published, in plain numbers: audits run $3,500–$8,500; sprints $12,000–$45,000, fixed quote in writing.
One build, drawn to scale.
Of the example builds on our homepage, this is the one that maps most directly onto a retail operation running on five systems that do not talk.
One operating view across the tools you already pay for.
Connects CRM, billing, and project software so the same job shows the same status everywhere. No more reconciling five screens by hand.
The win: one reliable picture instead of five that disagree.Illustrative builds, not client claims. What we’d actually scope is whatever your free assessment shows is worth automating first. The one build we can name is MARCUS, a private AI back office for a regulated lender.
AI for retail businesses.
Want the numbers?
The full price list is published — audits, sprints, managed services, all on one page.
Read the price list →01What can AI do for a retail business?+
Often the reconciliation across systems that do not talk — inventory, POS, and ordering — plus demand patterns and the repetitive back-office work.
02How much does it cost?+
The AI Readiness Audit runs $3,500–$8,500; an AI Implementation Sprint runs $12,000–$45,000, quoted fixed in writing before work begins.
03How long does it take?+
An audit is 2 to 4 weeks; a build is 4 to 12.
04Do you work remotely or on-site?+
We run two hubs — Denver, Colorado and Phoenix, Arizona — for in-person work, and we work remotely with businesses across the US. Same method, same fixed prices either way.
See the wins in retail.
30 minutes with a senior advisor who walks your inventory, support, and merchandising workflows and tells you what is worth automating, and what is not.