Proactive communication service event system

1 . A method, comprising:

aggregating, over a telephony network implemented by a software platform, phone data indicative of call connection quality for one or more phone devices associated with a customer of the software platform;

determining, based on the aggregated phone data, a service event affecting the one or more phone devices;

outputting, for display within a graphical user interface rendered at an administrator device of the customer, the aggregated phone data and a representation of the service event; and

changing, based on an input received via the graphical user interface corresponding to the service event, one or more telephony network resources of the customer.

2 . The method of claim 1 , wherein determining the service event affecting the one or more phone devices comprises:

identifying, using a machine learning model trained to evaluate the aggregated phone data, a pattern in the call connection quality for the one or more phone devices; and

corresponding, using the machine learning model, the pattern to the service event.

3 . The method of claim 1 , wherein determining the service event affecting the one or more phone devices comprises:

forecasting the service event by extrapolating a trend from the aggregated phone data.

4 . The method of claim 1 , wherein determining the service event affecting the one or more phone devices comprises:

determining that the aggregated phone data exceeds a threshold corresponding to the service event, wherein the threshold is defined for the customer.

5 . The method of claim 1 , comprising:

outputting, for display within the graphical user interface, a map illustration of a premises of the customer and locations of the one or more phone devices within the map illustration.

6 . The method of claim 1 , comprising:

training a machine learning model to identify or predict service events by evaluating patterns in data communicated over the telephony network via multiple customers of the software platform.

7 . The method of claim 1 , comprising:

determining a recommended action to perform to address the service event; and

prompting, within the graphical user interface, for the input based on the recommended action.

8 . The method of claim 1 , wherein the service event corresponds to a poor call connection quality for a high priority phone device of the one or more phone devices, and wherein changing the one or more telephony network resources of the customer comprises:

decreasing network bandwidth available to a low priority phone device associated with the customer; and

increasing network bandwidth available to the high priority phone device.

9 . The method of claim 1 , wherein the aggregated phone data corresponds to at least one of call log information, active call information, jitter measurements, packet loss measurements, latency measurements, or software version information for the one or more phone devices.

10 . A non-transitory computer readable storage device including program instructions that, when executed by a processor cause the processor to perform operations, the operations comprising:

aggregating, over a telephony network implemented by a software platform, phone data indicative of call connection quality for one or more phone devices associated with a customer of the software platform;

determining, based on the aggregated phone data, a service event affecting the one or more phone devices;

outputting, for display within a graphical user interface rendered at an administrator device of the customer, the aggregated phone data and a representation of the service event; and

changing, based on an input received via the graphical user interface corresponding to the service event, one or more telephony network resources of the customer.

11 . The non-transitory computer readable storage device of claim 10 , the operations further comprising;

generating a map of a premises of the customer, wherein the map includes locations of the one or more phone devices; and

outputting the map to the graphical user interface.

12 . The non-transitory computer readable storage device of claim 10 , wherein determining the service event affecting the one or more phone devices comprises:

transmitting, to a machine learning model trained to identify service events by evaluating patterns in data communicated over the telephony network via multiple customers of the software platform, a request to identify the service event, wherein the request includes the aggregated phone data; and

receiving, from the machine learning model, the service event, wherein the service event corresponds to a pattern identified within the aggregated phone data.

13 . The non-transitory computer readable storage device of claim 10 , wherein determining the service event affecting the one or more phone devices comprises:

predicting the service event by identifying a trend from the aggregated phone data corresponding to at least one of call log information, active call information, jitter measurements, packet loss measurements, latency measurements, or software version information for the one or more phone devices.

14 . The non-transitory computer readable storage device of claim 10 , the operations further comprising:

determining whether the service event corresponds to a high priority phone device of the one or more phone devices, wherein the high priority phone device is experiencing a poor call connection quality for;

decreasing, in response to a determination the service event corresponds to the high priority phone device, network bandwidth available to a low priority phone device associated with the customer; and

increasing network bandwidth available to the high priority phone device.

15 . A system, comprising:

a memory subsystem configured to store instructions; and

processing circuitry configured to execute instructions to:

aggregate, over a telephony network implemented by a software platform, phone data indicative of call connection quality for one or more phone devices associated with a customer of the software platform;

determine, based on the aggregated phone data, a service event affecting the one or more phone devices;

output, for display within a graphical user interface rendered at an administrator device of the customer, the aggregated phone data and a representation of the service event; and

change, based on an input received via the graphical user interface corresponding to the service event, one or more telephony network resources of the customer.

16 . The system of claim 15 , wherein the processing circuitry is configured to execute instructions to:

collect training data communicated over the telephony network via multiple customers of the software platform; and

train a machine learning model to identify or predict service event using the training data.

17 . The system of claim 15 , wherein the processing circuitry is configured to execute instructions to:

identify, using a machine learning model trained to evaluate the aggregated phone data, a recommended action to perform to access the service event, wherein the recommended action corresponds to the service event; and

output, to the graphical user interface, the recommended action.

18 . The system of claim 15 , wherein the processing circuitry is configured to execute instructions to:

decrease, in response to the service event corresponds to a poor call connection quality for a high priority phone device of the one or more phone devices, a first network bandwidth available to a low priority phone device associated with the customer; and

increase a second network bandwidth available to the high priority phone device, wherein the increase in the second network bandwidth corresponds to the decrease in the first network bandwidth.

19 . The system of claim 15 , wherein the processing circuitry is configured to execute instructions to:

define, for the customer, a threshold corresponding to the service event, wherein the threshold corresponds to at least one of call log information, active call information, jitter measurements, packet loss measurements, latency measurements, or software version information for the one or more phone devices, wherein to determine the service event affecting the one or more phone devices the processing circuitry is configured to execute instructions to:

determining that the aggregated phone data exceeds the threshold.

20 . The system of claim 15 , wherein, to determine the service event affecting the one or more phone devices, the processing circuitry is configured to execute instructions to:

evaluating the aggregated phone data using a machine learning model trained to identify or predict service events based on patterns in the call connection quality for the one or more phone devices.