Software Theories develops expert systems that make computers dramatically easier and more intuitive to use. We accomplish this by allowing users to interact with computers the way they would naturally expect to. Our systems are fundamentally built on user interviews, and our solutions take into account that the user may know very little about the solution or the problem.

We develop the following solutions:

Natural Interfaces

Natural Programming Systems

Why?

Software Theories was inspired by the realization that the primary slowdown in productivity, be it in software development or other fields, is information gathering. 

In software, this is easy to spot.  We constantly work in new technologies, with new libraries, under unique requirements.  Libraries attempt to provide some pre-built solutions, but we must spend the time to learn them.  Because they do not understand our specific requirements, we must figure out how to bend them to our needs.  Even after we manage to write our solutions, because we seldom are experts in the problem domain, we do not know if our methods are appropriate – if we created bugs, or vulnerabilities, or worse.  How many times do we find ourselves thinking, ‘If I knew what I know now, I could have done this in one tenth of the time’?

Even outside of software development, we find ourselves constantly wondering where options are buried, or worse – if these options even exist.  Learning a new application is not easy – we need to figure out the nomenclature, menu hierarchies, and methods of doings things.  Users often get intimidated by new software, refusing to switch to newer systems, frustrating software sales.  Even after we learn how, if the application is not something we use regularly, we’ll be challenged to remember next time we need it.

How?

Our proprietary technology, KES (Knowledge Encapsulation System), is the world’s first context sensitive natural language expert system.   Its primary goal is to reduce, as much as possible, the information required by a user to work with software.  It accomplishes this by:

Allowing the user to express their requirements in their own words

Eliminates the need to understand the problem domain, nomenclature, or solution space Provides the flexibility to allow both experts and amateurs to work together

Generating solutions based on an analysis of ALL the requirements

Allows the expert system to make ‘smart’ decisions for the user Allows the expert system to know what is not important, or what was not specified.