The Roam Travel thesis
More good days together.
Roam is building private AI agents that learn what your family loves, find the best memories per dollar and carry the details through. You bring the wish. You approve the decisions.
Start with a wish
“Disney with the whole family for Thanksgiving. We can move two days either way. Find the best memories per dollar.”
That should be enough to begin. With permission, Roam remembers who is going, what the family enjoys, how they like to travel and what worked last time. It asks what is missing or has changed, then gets to work.
Choose what is worth it for this family
MPD means memories per dollar. Roam should give each trip idea a score out of 10 for its expected value to your family: likely enjoyment and time together, weighed against the full cost, tiring travel and what could go wrong. Show which family priorities drove the score and how confident the estimate is, so the choice is easy to understand.
Learn from families like yours
Good advice often starts with another family’s experience. Roam is being built to keep names, ages and budgets in each family’s private record. Families can choose to contribute feedback about a trip, such as whether young children enjoyed a hotel or an extra park day was worth it. Roam would use patterns across similar families to help find the best memories per dollar for yours. Individual profiles stay private. Family data is never sold, and contributing feedback is always optional.
Carry the care through
AI agents should check the dates and full cost, confirm that the arrangements fit and follow up on unfinished work. A Roam advisor remains accountable. The family approves the spending, and a supplier confirmation makes each booking real. After the trip, ask what worked and what could be better.
Families deserve to own these agents and control their data. Each agent should be built around the family it serves, growing with them over time.
Start with a trip brief today. Your answers stay in your browser until you choose to share them. Private family memory, shared learning, scored comparisons and AI booking workflows are in development.