I used Tika to build a search engine prototype, and it was fantastic for getting us up and running quickly.
It's a really easy to use generic parser for a bunch of document types. The downside of being so generic and easy to use is that you end up lacking document-specific context that could be useful. For example: Do you consider the header/footer text to be important, or just noise (Page 1, Page 2, etc.)? Is the text contained in the Table of Contents or section headers important, or just the actual content? You won't find any ways to tweak the result, which could be a good or bad thing depending on your use case.
We ended up using it as our "fallback" parser, writing more contextually aware ones for document types of greater importance to our use case (PDFs were high on the list).
No customization applied, pointed at Hacker News: https://cse.google.com/cse?cx=37e5b152f44307b8a&q=%22search%...
Hacker News' own search: https://hn.algolia.com/?q=%22search+engine%22