Three products, one standard.
Every Machine Commerce product begins as an observation from the benchmark. We run AI shopping agents against real stores, and the failures those runs produce are too valuable to leave in a report. So they become products: one reads failure as lost revenue, one runs the standard continuously for a merchant, one turns the underlying catalogs into a data layer.
None of them are dashboards, and none of them exist apart from the research that produced them. Each one applies the standard inside a real business, generates new observations, and makes the next benchmark run smarter.
RevLeak
See where your store leaks revenue when machines shop it.
Runs agents against your store and prices every failure. Discovery breaks, checkout leaks, variants confuse: each one measured and ranked by revenue impact.
Defoe
The AI employee that audits your store every week.
Lives in Slack. Every week it runs the full audit suite, compares results with previous runs, and posts what changed, what broke, and what to fix first.
SKU Graph
The product graph for machine commerce.
Every store our agents touch becomes structured knowledge. Products, variants, prices, availability: the commerce web stops being pages and starts being a graph.
Run them on your store.
The fastest way to understand any of these products is to point one at your own store. We run the benchmark, walk you through the failures, and hand you the priority list. The data speaks first.
