Intelligent order problem learning and mitigation in automated order processing system
US-2023229737-A1 · Jul 20, 2023 · US
Systems and methods for managing customer job requests through job completion
US2025013957A1 · US · A1
| Field | Value |
|---|---|
| Publication number | US-2025013957-A1 |
| Application number | US-202318347687-A |
| Country | US |
| Kind code | A1 |
| Filing date | Jul 6, 2023 |
| Priority date | Jul 6, 2023 |
| Publication date | Jan 9, 2025 |
| Grant date | — |
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- Title
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Abstract
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In various embodiments, the present disclosure relates to managing customer infrastructure job requests through job completion. Steps include training a machine learning model with data associated with one or more customers of an infrastructure service provider; receiving one or more job requests from the one or more customers; identifying one or more insufficiencies in the one or more job requests based on the training; and performing one or more actions based on the identifying.
First claim
Opening claim text (preview).
What is claimed is: 1 . A non-transitory computer-readable medium comprising instructions that, when executed, cause one or more processors to perform steps of: training a machine learning model with data associated with one or more customers of an infrastructure service provider; receiving one or more job requests from the one or more customers; identifying one or more insufficiencies in the one or more job requests based on the training; and performing one or more actions based on the identifying. 2 . The non-transitory computer-readable medium of claim 1 , wherein the one or more actions include any of automatically remedying the insufficiencies and notifying the one or more customers of the insufficiencies. 3 . The non-transitory computer-readable medium of claim 1 , wherein, responsive to receiving a plurality of job requests, the steps further comprise: grouping the plurality of job requests based on the training. 4 . The non-transitory computer-readable medium of claim 1 , wherein the steps further comprise: opening one or more jobs in an Enterprise Resource Planning (ERP) system associated with the infrastructure service provider based on the one or more job requests. 5 . The non-transitory computer-readable medium of claim 4 , wherein the steps further comprise: providing a link associated with each of the one or more job requests to a web storage system, wherein the link is adapted to allow uploading of job data associated with each of the one or more job requests. 6 . The non-transitory computer-readable medium of claim 5 , wherein the steps further comprise: closing one or more jobs based on the job data uploaded to the web storage system. 7 . The non-transitory computer-readable medium of claim 1 , wherein the training includes any of supervised and unsupervised learning. 8 . The non-transitory computer-readable medium of claim 1 , wherein the data includes historical job request data. 9 . A method comprising steps of: training a machine learning model with data associated with one or more customers of an infrastructure service provider; receiving one or more job requests from the one or more customers; identifying one or more insufficiencies in the one or more job requests based on the training; and performing one or more actions based on the identifying. 10 . The method of claim 9 , wherein the one or more actions include any of automatically remedying the insufficiencies and notifying the one or more customers of the insufficiencies. 11 . The method of claim 9 , wherein, responsive to receiving a plurality of job requests, the steps further comprise: grouping the plurality of job requests based on the training. 12 . The method of claim 9 , wherein the steps further comprise: opening one or more jobs in an Enterprise Resource Planning (ERP) system associated with the infrastructure service provider based on the one or more job requests. 13 . The method of claim 12 , wherein the steps further comprise: providing a link associated with each of the one or more job requests to a web storage system, wherein the link is adapted to allow uploading of job data associated with each of the one or more job requests. 14 . The method of claim 13 , wherein the steps further comprise: closing one or more jobs based on job data uploaded to the web storage system. 15 . The method of claim 9 , wherein the training includes any of supervised and unsupervised learning. 16 . The method of claim 9 , wherein the data includes historical job request data.
Assignees
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Classifications
Needs-based resource requirements planning or analysis · CPC title
- G06Q10/06316Primary
Sequencing of tasks or work · CPC title
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Frequently asked questions
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- What does patent US2025013957A1 cover?
- In various embodiments, the present disclosure relates to managing customer infrastructure job requests through job completion. Steps include training a machine learning model with data associated with one or more customers of an infrastructure service provider; receiving one or more job requests from the one or more customers; identifying one or more insufficiencies in the one or more job requ…
- Who is the assignee on this patent?
- Etak Systems Llc
- What technology area does this patent fall under?
- Primary CPC classification G06Q10/06316. Mapped technology areas include Physics.
- When was this patent published?
- Publication date Thu Jan 09 2025 00:00:00 GMT+0000 (Coordinated Universal Time) (A1). Legal status and post-grant events are not shown on this page.
- What related patents are in patentsdb?
- We list 2 related publications on this page (citations in our corpus or others sharing the same primary CPC).