If there are current employees reading, they might be able to give a better answer than me. Basically, the project is to build a huge knowledge base of basic facts and "common sense" knowledge and an inference engine that could use a lot of different heuristics (including ones derived from semantic implications of contents of the knowledge base) to do efficient inference on queries related to its knowledge. One way of looking at Cyc from a business point of view is that it's a kind of artificial analyst sitting between you and a database. The database has a bunch of numbers and strings and stuff in a schema to represent facts. You can query the database. But you can ask an analyst much broader questions that require outside knowledge and deeper semantic understanding of the implications of the kinds of facts in the database, and then they go figure out what queries to make in order to answer your question - Cyc sort of does that job.

The degree to which it's effective seemed to me to be a case-by-case thing. While working there I tended to suspect that Cyc people underestimated the degree to which you could get a large fraction of their results using something like Datomic and it was an open question (to me at least) whether the extra 10% or whatever was worth how much massively more complicated it is to work with Cyc. I might be wrong though, I kind of isolated myself from working directly with customers.

One issue is just that "useful" always invites the question "useful to whom?"

Part of the tension of the company was a distinction between their long term project and the work that they did to pay the bills. The long term goal was something like, to eventually accumulate enough knowledge to create something that could be the basis for a human-ish AI. Whether that's useful, or their approach to it was useful, is a matter for another comment. But let's just say, businesses rarely show up wanting to pay you for doing that directly, so part of the business model is just finding particular problems that they were good at (lots of data, lots of basic inference required using common sense knowledge) that other companies weren't prepared to do. Some clients found Cyc enormously useful in that regard, others were frustrated by the complexity of the system.

Thanks for the reply. A 10% improvement in anything is usually immensely valuable but I know that you're using an arbitrary number in that 10%. I think the trick would be to make Cyc less complicated. It sounds like Cyc would do best sitting inside of a university or a foundation where they wouldn't have to worry about corporate clients. Or inside a massive tech company like Google where its budget would just be a drop in the bucket.

All the programmers at Cycorp, and most of the ones who've gone on to do other things, have a dream of re-writing the inference engine from scratch. Its just that those dreams don't necessarily align in the details, and the codebase is so, so, so big at this point that it's a herculean undertaking.