Marker

Companies want AI to transform how they work but most AI initiatives fail because the knowledge of how work actually happens lives in employees' heads rather than documentation. Leaders lack the time, expertise, and clear sense of what AI can realistically do, let alone how to get it into production. The usual responses do not solve this: doing nothing lets the gap compound, hiring the rare people with real experience takes quarters, and typical consultancies ship something but then leave. The founders say they saw this problem firsthand from inside Gap, where they ran the Office of AI.

Marker embeds directly with a client's teams to learn how work actually happens, then builds custom AI agents on what it calls the Marker Command Center. Agents are designed to work within the tools teams already use, such as existing spreadsheets, reports, and queues, so there is no new software to learn. The engagement follows four stages: understand how work happens, evaluate and rank opportunities by cost, capacity, speed or growth, build and ship agents into production within weeks while escalating ambiguous cases to a human, and then compound by shipping each subsequent system faster than the last. Marker states it stays embedded with clients rather than delivering a single one-off agent.