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Worth clarifying that we don't do any of this - we absolutely don't scrape the data of your 1st degree connections or anyone else; only leads that you explicitly query.

Email addresses are then verified using sources in the public domain.

I agree that this is all certainly worth emphasising further and I think we could do with further clarification points in the FAQs.

Finally, we originally built this as an internal tool, but decided to wrap it up as a public facing one.

Our users really are across a bunch of different industries. That's the thing - this is such a widespread problem that it's not constrained to one space. Data from Saleforce -> Mixpanel; eBay -> Shopify; NationBuilder -> centralised data warehouses are some examples.

Thanks for asking.

We're very much focussed on automating the process of getting rows and rows of data out of one system and into another. (e.g. transfer all of today's sales data from one platform to another)

IFTTT is much more event-based (e.g. when I receive an email from person x, send me a text)

Thanks for sharing!

The focus is much more on people who are currently running existing, manual processes in spreadsheets (e.g. monthly reporting) and has much less of a database element. For example, we don't do any of the "loading" stage in a typical ETL process.

This is an awesome concept- I always find myself trying to get the best deals. The biggest issue for me is the upfront fee. A percentage of final savings would be far preferable.

Thanks for the feedback. The big pain point we are focussing on is when you are given someone else's spreadsheet that you are not familiar with. It then can take hours to get your head around how they have put it together.

In this regard, Slate is most useful as way of semi-automatically documenting the spreadsheet.

We made the Iron Man example specifically for HN - possibly not the best thing to pitch big financial firms with - fair point!