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@ashley_from_shadow thank you for the support! Our AI chatbot is great at getting you last-minute tips.
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You know, why I like this one. I really loved for travelling. But I need to find and go amazing places to see. So I need best and latest information of that place . So this tool is amazing for my hobby. Good work team.
@lahiru_dilshan_chandrasiri1 thank you! Please let us know if you have any feedback as you plan your trips with Guide!
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As I write the Everything AI in Travel newsletter I've tried pretty much all the AI travel planners that have come out. I use the same trip for all of them to be able to compare - a trip I actually did with my family last July in Borneo. Tried it on Guide.com and there were a few issues. First up Borneo in Malaysia wasn't an option? Happy to provide private feedback to the team if they want some more detail.
@discover_drives thanks for trying out Guide! Good catch on Borneo. At the moment we'd have to search for a specific city in that island - working on improving this though! Would love to chat to get more detailed feedback. What's the best way to reach you?
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Does Guide use Lonely Planet data for routing order too, or just for place recommendations? The London feedback in the comments is a common AI itinerary problem... models pick great spots but ignore geographic clustering. If you're already pulling location coordinates from Lonely Planet and Google, grouping by proximity per day would fix most of the backtracking.
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Every data team I've worked with ends up with lineage living in one tool, docs in another, and a metadata spreadsheet nobody updates. Secoda collapsing catalog, lineage, and documentation into one workspace removes the stitching. The no-code monitors for data quality checks are a nice touch since most teams skip quality until something breaks in a dashboard.
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Does Guide use Lonely Planet data for routing order too, or just for place recommendations? The London feedback in the comments is a common AI itinerary problem... models pick great spots but ignore geographic clustering. If you're already pulling location coordinates from Lonely Planet and Google, grouping by proximity per day would fix most of the backtracking.
Every data team I've worked with ends up with lineage living in one tool, docs in another, and a metadata spreadsheet nobody updates. Secoda collapsing catalog, lineage, and documentation into one workspace removes the stitching. The no-code monitors for data quality checks are a nice touch since most teams skip quality until something breaks in a dashboard.