SourceShelfPrivate AI workflow example
Your research. Your trip. Your choice of AI.
Collect travel guides, hotel information, transportation details, and personal notes into SourceShelf. Then explore your research with AI while keeping your information private.
The research problem
Planning a trip usually means collecting useful details from many places, then trying to remember which tab, download, or note contained the answer.
One focused workflow
SourceShelf turns research gathering into a deliberate sequence: collect what matters, group it for the trip, then let a compatible AI app work from that selected context.
The demonstration pack
For this demonstration, SourceShelf was used to collect a fictional Japan trip research collection including travel guides, transportation information, food recommendations, and personal preferences.
Demonstration note: The names, prices, schedules, venues, and recommendations shown here are fictional.
Product evidence
These are actual responses from the demonstration—not fabricated interface mockups. The compatible AI app searched the selected SourceShelf pack and answered from its travel research.
The answer combines the trip’s pace, cultural priorities, public-transit preference, budget, and saved destination research into one coherent route.
Actual demo response · SourceShelf pack connected read-only
The recommendation selects Ueno after weighing the saved neighborhood guide against the travelers’ preference for culture and a balanced pace.
Actual demo response · Sources consulted through the pack
The answer compares Tokyo neighborhoods and Kyoto versus Okinawa using the saved goals, logistics, weather tradeoffs, and fictional budget.
Actual demo response · Research synthesized across sources
Start with the sources you trust
Bring the research you already collect into one private, portable workflow—then use the compatible AI app and model you choose.
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