Kyield Technology While Kyield Enterprise is most closely associated with Business Intelligence (BI) and Operational Intelligence (OI), the holistic system design is made possible due to data convergence, with highly specific functionality in several segments of the previous generation of enterprise software, including BI, Search, MDM, Performance, and Productivity. The Kyield system design is covered in part by an AI systems patent awarded to Montgomery in 2011, which is partially depicted in the diagram below.
The CKO Engine is the most complex component in the Kyield Enterprise design. Appropriately compared to a semantic enterprise operating system, semantic layer, enterprise server, and/or a master data management system, the CKO Engine actually contains elements of each. The combination of the structured data, system design and applications allows the entire organization to self-manage their digital work environment within the corporate parameters and mission of the organization. To optimize Kyield for the organization, the CKO Engine can be integrated with communications, human performance, and productivity suites. While a Chief Knowledge Officer title is unnecessary, we do provide training and certification for the administrator of the CKO Engine directly and through approved partners with expert guidance during the pilot phase and as needed thereafter.
Permissions for all modules in system
Parameters for all modules in system
Security & rules for entire system
Automated audits & reporting
System-wide algorithms & ratios
Alerts for risk & crisis prevention
Baseline predictive across system
Integration with pre-installed systems
The Group Module serves as the administrative tool for business groups, large teams, and partners. The Group Module enables groups to customize their data consumption, work flow, communications, and business intelligence to the specific needs of the business unit or team. It also allows business unit managers to manage relationships internally and externally, refine human performance metrics, employ algorithms and ratios within the parameters set by the CKO Engine, and adapt to regional regulatory, language, and culture issues. The module can adapt continuously as necessary within the parameters set by the CKO Engine and can be managed by an operations manager with no technical expertise and minimal training. The Group Module is designed to provide the business unit with the adaptive data management they need to optimize teams and leverage data analytics and workflow to achieve their goals.
Tailor analytics to each group
Curriculum for projects & goals
Enable new teams & individuals
Optimize queries & streaming
Visually interpret metrics for group
The Individual Module is in some respects the most important part of the Kyield system as organizations are dependent upon individuals for every aspect of the operation. Most of the discovery, intellectual capital, innovation, opportunity, risk, and prevention can be sourced to individuals in some manner, but IT systems are generally designed to only exploit individuals, not optimize and empower them. While the Individual Module must work within the regulatory, policy, legal, and mission parameters in the digital workplace, each individual in the Kyield system is provided more adaptive function at higher levels than any known system. This can be achieved due to a combination of the rich semantic intelligence in the Kyield system, the functionality of the CKO Engine, Group Module, Individual Modules, and how they interact.
Tailored streaming content
Tailored queries & returns
Color coded work metrics
Semi-auto & full-auto options
To your left is a recent diagram in stack format which is a common method to visualize IT system components. For customers of our pilot program we tailor all of the documents to the specific organization as part of the planning process. Like most enterprise systems, the Kyield pilot timeline and cost is dependent to a large extent on what the customer organization has installed, extent of data prep involved, whether new programs will be necessary, and how extensive integration will be with pre-existing applications, degree of interoperability, and other factors.
It's important to understand that the data standards increasingly range from chip to chip and extend throughout the technology stack, including Kyield functionality and applications, which is why we use the term semantic fabric rather than layer.