I wouldn't discount your product's usefulness for simple datasets. As a UX guy I'd love to see this put toward a better ecommerce search/browse -- "Desk chairs between $150 and $225".
I see it augmenting the standard facet-filter style browse. For example http://nymag.com/restaurants/: I enter "indian food in the east village" -- your product helps pre-arrange the facet filters for me, but I can still add a price range or another neighborhood to the query through standard UI.
The obvious benefit is that natural language browse offers quick access to complex queries (within the user's mental model). But if the results are presented well, your product can be used to train the user to understand the mapping between natural language and executable query (and in that way inform their mental model).
If that means that some users only need to use the natural language feature a few times (before switching to standard UI), it's still successful.
I see it augmenting the standard facet-filter style browse. For example http://nymag.com/restaurants/: I enter "indian food in the east village" -- your product helps pre-arrange the facet filters for me, but I can still add a price range or another neighborhood to the query through standard UI.
The obvious benefit is that natural language browse offers quick access to complex queries (within the user's mental model). But if the results are presented well, your product can be used to train the user to understand the mapping between natural language and executable query (and in that way inform their mental model).
If that means that some users only need to use the natural language feature a few times (before switching to standard UI), it's still successful.