IBiS company

IBiS company

Knowledge-based (KB) systems development

We have been using rapid prototyping and short scale iterative development techniques for over 15 years. These techniques (now referred to as "close development" and "extreme programming") enable developers to acquire more accurate information about the system requirement before development. We spend more time with the experts and users of the system to ensure that we develop the real requirement.

Your experts make expert decisions. Intuitive decissions are often though to be too complex to capture but, given a expert who can explain the circumstances under which certain decisions are made, we can emmulate those processes and enable their knowledge to be disseminated. Where the rules are already documented we can formulate the "rule book" into interactive business rule systems to ensure completeness and consistency.
In order to explain the advantages of these systems, we have detailed below where we believe they can provide better solutions.

It is rule based Regulations, company guidelines and specialist rules-of-thumb can be encoded and distributed.
It involves analysis Situations may have several possible explanations, or options must be ordered.
The rules change frequently Some applications are beset by ever-changing rules for which traditional programming is too costly.
It is performed infrequently Mistakes easily occur in tasks which are undertaken rarely, and simple errors can multiply.
It requires more rapid decision making Sometimes the task rules are too complex for a speedy human decision.
It uses dynamic data Where the input data is rapidly changing, early awareness of underlying trends can be vital.
It involves inexact data Apart from some science, engineering and finance, the bulk of day-to-day decision making is qualitative.
Consistent judgements are needed In decision making, analysis and diagnosis.
Retaining expertise In the event of loss of key personnel, their unique talents can be retained.
Repeated decision making is required Decisions required often but at a fairly trivial level, can lead to boredom and error.
Integrating existing systems Reducing the need for manual intervention
closing "gaps" in current systems and evaluating data.
Expert analysis of corporate data
Data-mining To maximise its value, and to direct it to the appropriate personnel.

It is rule based	Regulations, company guidelines and specialist rules-of-thumb can be encoded and distributed.
It involves analysis	Situations may have several possible explanations, or options must be ordered.
The rules change frequently	Some applications are beset by ever-changing rules for which traditional programming is too costly.
It is performed infrequently	Mistakes easily occur in tasks which are undertaken rarely, and simple errors can multiply.
It requires more rapid decision making	Sometimes the task rules are too complex for a speedy human decision.
It uses dynamic data	Where the input data is rapidly changing, early awareness of underlying trends can be vital.
It involves inexact data	Apart from some science, engineering and finance, the bulk of day-to-day decision making is qualitative.
Consistent judgements are needed	In decision making, analysis and diagnosis.
Retaining expertise	In the event of loss of key personnel, their unique talents can be retained.
Repeated decision making is required	Decisions required often but at a fairly trivial level, can lead to boredom and error.
Integrating existing systems	Reducing the need for manual intervention
closing "gaps"	in current systems and evaluating data.
Expert analysis of corporate data Data-mining	To maximise its value, and to direct it to the appropriate personnel.