FAQ

Pradjna™ is based on a revolutionary Machine Learning framework. This platform can be considered a scaled down version of the human brain with appropriate level of intelligence. The sensors in the glove collect the data directly from the context - example welder data is collected from the actual welding conditions and is based those parameters that contribute to our perception of good welding performance like proximity, weld_progression, travel_angle and work_angle etc..

Currently to evaluate a welder you need another individual. Sometimes this is done by an expert individual in a formal testing environment.. Or for a professional welder, this is involuntarily the job of the supervisor. No one authorises the supervisor in this case, but the perception of the supervisor becomes a crucial determinant of customer satisfaction. So it becomes imperative to have a robust, continuous and objective methodology more specifically in the case of a commercial operation like manufacturing facories or companies.

Now in a business case like Usage based Insurance, currently Indian insurance companies have no viable option to evaluate best practices of welders to qualify them for rebates in their indusrial insurance premium. American UBI model is not viable here in India because the premiums are low and there is not enough margins for a high cost solutions. In this case Pradjna™ can provide an optimum solution that is both sufficiently accurate and cost effective.

We understand that every individual context is unique.So we try to ensure that every evaluation reflect that unique characteristics without loosing objectivity. Thus we have designed an approach to bench mark the evaluations against baseline evaluations completed in the same context. We also normalize the individual data over a large numbers of evaluations and also capture a significant amount of data for each evaluation. We have also made sure that our architecture takes care to ignore outlier values in the sample.

Currently there are no companies in India offering motor skills assessment service based on Artificial Intelligence. Large corporations have the constraint of their own proprietory HR and performance management processes. It is not possible to tweak them for our platform. This is where the importance of PaaS comes in - we can easily provide programmatic interface to these systems to input and output appropriate data streams. This makes it much more effective and simplified to use our services. For those medium, small companies without their proprietory systems a standard interface is available.

We offer multiple options based on the requirement. For small and medium enterprises and for those with lower usage, we can provide a per user service. For larger users we have the annuity model with a flexible ceiling for usage. We can also look at a comprehensive business process suite to handle your diverse performance management needs. Please get in touch with us - info@pradjna.in - to know more about our pricing plans.

In the case of a per head pricing model, it is fairly straight forward. Once you finalize your requirement, we can provide the access to your contact person/s who can configure the access to themselves and to candidates within our system. The candidates need to wear the glove while doing welding work. Once they are setup in the system, candidates can log in and start work. Data and reports and created and can be seen by authorised users or be mailed to them or both.

In the case of annuity model, we need to study and finalize the pricing plan. User access needs to be set up for each geography if the company has operation across multiple cities. We will also configure the appropriate benchmarks. The candidates can be imported into the system and access set up. They can then wear the glove and start using them. We will also finalize the reporting process and configure the infrastructure accordingly.

We will assign individual support persons to your engagement. They will be available Monday through Friday during office hours 9:30 - 5:30 on mail based support for standard engagements. For annuity model we can work through the support model on a case to case basis.