Claims:CLAIMS
We claim;
1. An apparatus having modularly intercoupled device having an apparatus for prognostic based identification and its status renewal of contracts through artificial intelligence, the apparatus comprising:
a. at least one system and device;
b. at least one customer and manufacturer;
c. at least one machine or equipment;
d. at least one database of all customers and machines;
e. at least one mobile device both at customer and manufacturer location;
f. at least one mobile device;
g. at least one cloud and client server with interface;
h. at least one adaptive deep learning tool with convolution pooling layer at server and client location;
i. at least one reinforcement learning module and
j. at least one analytics software module is modularly connected to a live cloud server by wired or wireless or hybrid connection methods with one to one or many to one or many to many possible connecting topologies.

2. The apparatus of claim 1, where in manufacturer has sold similar or dissimilar equipment’s directly to one or several customers or through a dealer network (distribution network) with contract agreements.

3. The machines of claim 2, where in the end customer may have procured the machine either through outright purchase or on long-term lease with contract agreements.

4. The machine of claim 3, where in contract customer and manufacturer mutually sign agreement by addressing free warranty duration on product, renewal period and so on.

5. The apparatus of claim 1, where in the hybrid deep convolution neural network module would adaptively train itself by taking all input parameter associated with each customer right from sales, various services provided to the customer under free warranty and contract period.

6. The apparatus of claim 5, where in the hybrid the deep neural network module has modularly connected analytics tool.

7. The hybrid deep neural network of claim 6, where in the hybrid neural network has an embedded reinforced learning mechanism to throughput the optimum and best contract to be renewed with various customers with return on investment output in multimedia form.

8. The adaptive learning module of claim 7, where in the module can be installed at customer or manufacturer or dealers or third party business analytics providers servers.

9. The claim claimed in 1, where in contract renewal with analytics in multimedia form with various updates contract renewal of client 1 to N by an email, AI chatbot Telephonic call, Face to face Database of all customers and machines Admin mobile device

10. The apparatus claimed in claim 1, where in single or part of the modules can be modularly embedded in any similar contract renewal product and solutions, where in it will adaptively generate a set of models, based on pre-history, general product history from the product manufacturer, warranty renewal duration, cost involved in warranty period, geographical locations and other direct and indirect cost parameters and provide optimum contract renewal strategy and solutions.

, Description:FIELD OF THE INVENTION:

Embodiments of the invention is generally relate to a system and method for the identification of contract and its status renewal by an adaptive artificial intelligence technique and methods.

BACKGROUND
In the connected internet world, the way in which we do business is changing rapidly due to advancement of new technologies and its effective implementation. Contract renewal is one such vertical in which product owners should adapt novel methods to increase their overall profit. There is a growing need for service business to repair and do the preventive maintenance of equipment to improve the equipment overall life cycle as part of service contracts. Many customers sign the service contracts with product manufactures to avoid the longer shutdown of equipment and improve the equipment lifetime with preventive maintenance. Service contracts are very critical for the equipment companies’ revenue. To overcome this issue, we have come at with novel system and method for the identification of contract and its status renewal by an artificial intelligence technique and methods.

SUMMARY
Embodiment of the inventions related to a modular design approach based a system and method for the identification of contract and its status renewal by an artificial intelligence been proposed.

In a further embodiment, customer contract renewals are very critical for revenue growth. Complex equipment requires specialist tools and personnel to carry out repairs when equipment fails. The equipment generates revenue to the customer, over the life of the equipment, when it is in working state, and no revenue when it is in failed state. Hence, the duration for which the equipment is in failed state is critical for the customer. Companies must spend lot of time to develop analytics to extract the data from different sources to check the contract renewals, Equipment’s/Assets that are out of contracts.

In a further embodiment, an adaptive artificial intelligence engine would automatically renew or provide priority based contract renewals with predictive analysis based on customer perception and contract usage. Contract renewal report provides the details which customers did not renew the contract and which customer will not be going to renew.

In a further embodiment, in one of the contract renewal logic is by filtering all service contracts, which are going to expire for specific month and out of which, how many contracts has been renewed and updated percentage of the contract renewal rate. If contract has been renewed in the later months then the contract renewal rate is updated in the contract expiry month.

In a further embodiment, one of the analytics modules would provide warranty conversion rate report; percentage of warranties converted to a service contract up to 90 days after the warranty expiration date (standard and extended warranty).

In a further embodiment, the following logic may be used; Filter the ZWAR (Warranty) contract types and show the number of contracts which are expired in 90 days and which are converted to service contract after 90 days, ZWAR contracts types and get the equipment’s associated with that contracts, Then Pass all the equipment’s and check any WV contracts has been created for that Equipments.

In a further embodiment, Customer Contract Predictive analysis (CPAs) is a key service metric that measures the time spent on assets that are covered on a service contract from the customer’s perspective of service touch time i.e. Field Service On-Site, material consumed and Technical Support time. This metric based decision is used to identify service contracts at risk for cancellation based on the amount of customer touch time (CTT) that has been provided for a contract date range. Contract Predictive analysis AI drive based on below algorithms.

In a further embodiment, predictive algorithm would also provide information such as customer contract value, Customer Service visits, material, travel , Cost of service contract and age of the equipment and so on.
BRIEF DESCRIPTION OF THE DRAWINGS
Features and advantages of the example embodiments, and the manner in which the same are accomplished, will become apparent with reference to the following detailed description taken in conjunction with the accompanying drawings.

FIGURE 1 is a diagram illustrating a cloud-computing environment based “an apparatus for identification and its status renewal of contracts through artificial intelligence” in accordance with an example embodiment.
FIGURE 2 is a diagram illustrating reinforcement learning with Convolution Neural Network (CNN) implementation of the invention.
FIGURE 3 is a diagram illustrating a contract renewal with analytics in multimedia form with various updates.
These and other objects, features and advantages of the embodiments of the invention will become apparent from the following detailed description, which is to be read in connection with the accompanying drawings.

DETAILED DESCRIPTION
Principles of the present invention include a systematic approach based product of an apparatus for prognostic based identification and its status renewal of contracts through artificial intelligence proposed at appropriate locations.
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Reference is made to FIGURE 1, which illustrates an exemplary embodiment of an apparatus for prognostic based identification and its status renewal of contracts through artificial intelligence, in which Cloud ( server, webserver, server AI tool) 125 is modularly connected to Device 100 ,Database of all customers and machines 115, Customer_1 130, Customer_n 135, Client mobile device 140, and an admin mobile device 120.

In a further embodiment, the machine or an equipment manufacturer has sold his product to several customers 130 to 135 at several locations across the globe.

In a further embodiment, the manufacturer and customer have stored their product details, contracts, product warranty and other terms and condition in their own computer database. Each of them have their own control and view mechanism devices Client mobile device 140, Admin mobile device 120 to see the status of the machine and contracts.

In a further embodiment, FIGURE 2. describe the reinforcement learning with convolution neural network implementation of the invention,
In a further embodiment, the adaptive learning artificial intelligence tool adaptively model all the machines Modelling of equipment 1 for customer 1 to N 200, its contracts both at customer and manufacturers servers.

In a further embodiment, the Convolution and pooling layer 210, Convolution and pooling layer 215, Fully connected layer 220 are used to train the model and saturates once error threshold level is reached.

In a further embodiment, for optimum warranty contract renewal reinforcement based neural network technique is used primarily it has modules such as Agent 250, Actions (at) 255, Environment 260 by taking into consideration of the penalty scores for set of contracts and clients 225 at time T=t0, next Run a policy 235, find an Observations 240, it its success full then Reward 245 the reference output,

In a further embodiment, the If the results are optimum 265 then best renewal options for the manufacturer 270 in text, audio or video formats.

In a further embodiment, the FIGURE 3: contract renewal with analytics in multimedia form with various updates.

In a further embodiment, the Contract renewal client 1 to N 300, updates are done through an Email 310 or through AI chatbot 315 or by calling the customer Telephonic call 320 or by meeting Face to face 325 or any combination thereof.

In a further embodiment, the deep neural network architecture would automatically generate reports based on product manufacturer, dealer and an end user inputs. These reports are based on various types of service one can replace; repair terms with new extended warranty clauses, primarily based on associated cost factor.

In a further embodiment, the proposed tool would rewrite the new renewal contract and provide several additional warranty clause options for the customers.

In a further embodiment, the AI tool may provide discount for long-term warranty conversions, too early warranty conversion and payment discounts.

In a further embodiment, the wherein our proposed novel artificial algorithm based tool would identify type of contact or model of the machine, profile based grouping of various similar and dissimilar product and solutions sold to one or several end users across geographical locations.

In a further embodiment, the Analytic report would provide every detail along with pros and cons associated with each contract renewal with respect to previous year in multimedia form.

Advantages of the invention are that such a mechanism is easy to user and affordable in terms of cost and results in at least about 635 savings.