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On top of iKen Studio we have developed various methodologies, models and prototypes for quick application development in various categories. Our focus is to value-add existing software products and solutions by enabling intelligence in them. This intelligence
includes knowledge automation component,
is agile, real-time and works on operational databases.
Some of the application domain we have expertise in include:
Adaptive (personalization, recommendation and match) Technology
A powerful state-of-the-art recommendation, matching, discovery and personalization framework supporting many kinds of products, structured contents and generic transactions seamlessly and uniformly; based on social (collaborative) filtering, content (logical and contextual) filtering, intelligent matching and on individual tastes along with adaptation to time (when user likes what) and location (where user likes what) dimension.
This framework works in real-time, self-learning and is completely programmable, configurable and customizable based on products, contents and required functionality. It can be customized, configured and built-in in enterprise solutions like ERP, CBS (Core Banking Solution), CRM (Customer Relationship Management), CMS (Content Management Solutions including web-based), KM (Knowledge Management) to have built-in personalization, recommendation and match capabilities.
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Intelligent Match Technology
A matching technology backed by AI techniques to intelligently match requirements (based on selected parameters, importance, objectives and constraints) v/s contents (like electronic gadgets, cars, resumes, profiles etc.). It also matches content v/s contents to get similar products/contents, etc. Gives the best to least matching results at more abstract and conceptual level rather than match based on keyword or exact (attribute/parameter) value-to-value or database query matching.
It can also configured to find out cluster having homogenous
(contextually and logically similar) contents based on matching features. This helps to show similar contents logically matching with selected content e.g
Similar Cars, Similar Resumes. The technology can
be configured to learn and adjusts importance of features, their weights and so on user interactions.
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Customer and Transaction Analytics
Most of the applications such as Anti-Money Laundering, Credit and Insurance underwriting, Fraud Management involve critical assessment and risk management based
on customer information and on-going transactions (which includes activities also). Our analytics framework defines and models the customer and transactions in generic way. It can be enhanced with domain knowledge, customized and configured based on application perspective and context. Our framework defined customer and transaction analytics in broader sense which includes four major components: a. customer profiling and assessment, b. customer personalization, c. transaction risk management, and, d. reporting mechanism.
Our technology combines power of explicit human domain knowledge (enabling conversion of tacit knowledge into explicit knowledge), and, implied knowledge learnt from past cases to understand patterns, associations, clusters etc. It can be modeled, configured, automated to work in real-time on on-going and pro-active basis rather than doing post-mortem analysis. It also supports CBR based fuzzy, qualitative and contextual matching engine to address better risk management unlike conventional business rule engine which are based on business rules.
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Knowledge Automation Technology
There is lot of information available within the organization in the form of manuals, documents, books, reports and so on. This information is either created internally by the stakeholders or obtained from external sources. Most the information available is in descriptive fashion, an user of that system needs to understand and make sense of it before making use of it. Same as that of documented information and knowledge, employees in the organizations have lot of precious knowledge and information in their minds. Organizations can benefit from tacit knowledge if they can convert into some explicit form so that it benefits other employees in the organization as well as customers of the organization. Knowledge automation techniques can facilitate the mechanism of converting expertise into more reusable and sharable actionable knowledge.
There are many systems which needs such human expertise automated to help internal employees as well as customers. These include: advisory and recommendation systems, technical help-desk for trouble-shooting and diagnosis, intelligent information search, intelligent tests and examinations and so on.
A technology based on expert system and case-based reasoning to convert tacit human expertise into explicit knowledge. This technology facilitates to create, share, disseminate precious expertise (internally as well as externally) available in the organization.
Business Rule Management
Many applications need to dynamic business rules which may be compliance rules, decision rules and so on. This is to make sure that all organizational activities are consistent and according to compliance. Centralised configured rules bring lot of consistency and objectivity across the organization. Rules can also be distributed to take care of local decision needs.
Our technology uses the combination of rule-based expert system and CBR technology. Only rule-based engines match rules exactly with given facts, even slight deviation from one of the criteria fails the rule. CBR-based matching allows fuzzy kind matching rather than exact match which filters data even with deviations. Data from various databases (integrated or merged) can be extracted on the fly and rules/rule-filters can be applied on them.
We are targeting software product and solution vendors who are looking to value-add their products and solutions by making them intelligence-enabled. We can help them to enhance and value-add to their products with AI capability to have in-built intelligence, knowledge automation and decision support capabilities.
There are many software products which automate well defined business processes but lack intelligence capabilities. Adding specific intelligence in such product can have many advantages. There are many software that automate specific organizational needs such as inventory management software, hospital management software, payroll systems and so on. Such systems can have built-in knowledge component.
Following examples show how such systems can be made intelligence-enabled.
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How
can it be intelligence-enabled
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- By incorporating decision rules to dynamically decide reorder quantity and alert depending upon types of goods and quantity.
- Automated learning to understand patterns (like time specific: which goods are sold, when, how much etc.) to optimize inventory.
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- Patients records can be automated to build repository of diagnosed cases. This can assist doctors in diagnosing new patients having similar kind of illness or diseases. Helping in knowledge reuse (even by new doctors) and justification through precedent.
- Optimizing and better management of hospital resources by understanding patients patterns (when, how many, what type of, what kind of illness/disease, etc.).
- Automating reporting systems: knowledge-based expert systems can be developed to interpret various results of medical tests such as blood test. This can save doctors time on routine interpretation and explanation to the patients. Patients can get automated advice.
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- One of the major issue with payroll systems is having too many options (salary structures for different kind employees, leave management, incentive and reward schemes) and frequent revisions based on HR policies and so on. This may need to modify the system on frequent basis unless it is highly parameterized with lot of options. Such options and revisions can be better managed using rule-based systems which allows decision rules to change on dynamic basis rather than hard-coded programming logic.
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- LMS solutions can be made more interesting to the learner as well as to the teacher/expert by incorporating human intelligence in them. For example, automated computer-based training (CBT) can be made more individualized like human tutor adding considerable flexibility in presentation of material and a greater ability to respond to idiosyncratic learners needs. Such systems are highly effective at increasing learners' performance and motivation.
- Computer adaptive tests (CAT) can greatly help to judge candidates compared to same kind of tests asking questions one by one in serial order for all. The questions can have attributes like difficulty level, average time to solve it, etc., based on these attributes the rules can be written to change the sequence from one level to another based on candidate's performance. The results can be analyzed (like average how long it took to solve question, how many could solve it) to fine tune attributes of questions.
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Functional information systems represent category of software those implement functional information systems such as human resource management, financial and accounting management, order processing, marketing and sales automation and so on.
- Apart from automating manual HR processes, some expertise can be automated such as employee assessment for a particular job.
- Intelligent matching technology can help to get the right candidate for right job to reduce attrition rate.
- Computer adaptive on-line technical, domain, soft-skill and psychological tests to do on-going assessment.
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- Apart from automating manual HR processes, some expertise can be automated such as employee assessment for a particular job.
- Intelligent matching technology can help to get the right candidate for right job to reduce attrition rate.
- Computer adaptive on-line technical, domain, soft-skill and psychological tests to do on-going assessment.
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Similarly enterprise level systems such as CRM
(customer relationship management) , ERP (Enterprise Resource Planning),
CBS (Core Banking Solution),
EMS (Enterprise Content Management) and so on can be made intelligent by incorporating intelligence in them.
Apart from value-addition to software
products, iKen Studio can be used in various
solutions like Anti-Money
Laundering, Call
Centre Applications, Determining
Dynamic Pricing, Retail.
Value-add existing software products and solutions
We can help software vendors to enhance and value-add to their products with AI capability to have in-built intelligence, knowledge automation and decision support capabilities. This will give software vendors competitive advantage and benefit to position their products better compared to competitors whose products don’t have these capabilities. Also their clients will be willing to pay more because of value-added functionalities.
Offer world's first AI SaaS Platform
We have world’s first integrated AI-software that can be delivered in SaaS mode: applications using our software can be developed and accessed from anywhere with ease e.g. one of alliance partner has developed credit rating application on mobile (and accessing it using Web Services) using our SaaS platform as back-end. This application we jointly developed sitting at different locations. This saves lot of time, man-power and help in faster application development.
Have hybrid technology and integrated development
We have hybrid AI technology rather single AI technology, it can address many types of application requirements of clients so they need not look at many other tools. Various extensions (methodologies, models and prototypes) have been added based on problem categories which gives tremendous advantages over other tools to develop and deploy solutions relatively quickly. We maintain only one version of our core framework, so whenever we add value to our core product, it would be automatically available to our client software vendors. Same framework is used for development, analysis, implementation and configuration unlike analytics tools like data mining that help in analysis only. It provides great degree of flexibility in modeling, customization and configuration. The software vendor need not buy them separately thereby saving on cost aspect.
Focus on tailor-made intelligence
Since our focus is on developing tailor-made solutions for specific needs rather than selling our core framework: iKen Studio, cost will be one of the major advantages (pay per need/required functionality) as vendors we are targeting need not bear the cost of buying, managing AI products, related skilled manpower, etc. Our clients can also benefits from our expertise that we have gained through developing solutions for other vendors.
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