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GPTfy - Salesforce Native AI Platform

Stop Guessing. Detect Root Causes.

GPTfy reads case comments, anonymizes the data, and returns probable root causes and corrective actions directly on the Salesforce case record.

Support agents spend too long manually parsing case comments to understand the problem. This demo shows how GPTfy runs root cause analysis in one click — delivering a structured problem statement, likely causes, and next steps without any manual investigation.

Capabilities shown in this demo

Problem Identification

  • AI reads all case comments to determine what the customer is actually experiencing.
  • Produces a concise problem statement so agents start with clarity, not confusion.

Root Cause Listing

  • Returns a structured list of likely causes that commonly lead to the identified problem.
  • Helps agents skip the diagnostic guesswork and move directly to investigation.

Corrective Actions

  • Suggests specific next steps agents can take to resolve the case.
  • Converts unstructured case comment data into an actionable resolution plan.

Data Anonymization

  • PII is masked from case comments before data reaches the AI provider.
  • Results are returned securely to the case record without raw data leaving your org.

Use this video when

A support agent receives a complex technical case and needs a structured starting point before calling the customer

A high-volume call center wants to reduce average handle time by eliminating manual case investigation

A service manager wants agents to enter each case with a pre-built troubleshooting path rather than starting from scratch

A team handling escalated cases uses AI root cause output to prepare before routing to a senior engineer

An ops team wants to automate root cause detection so the analysis is ready the moment a case is assigned

A quality team audits root cause patterns across resolved cases to identify recurring product or process failures

Frequently asked questions

GPTfy reads the case comments on a Service Cloud record, anonymizes the data, and sends it to an AI model. The AI identifies the problem the customer is facing, lists likely root causes that commonly lead to it, and suggests corrective actions the agent can take — all without manual troubleshooting.

GPTfy anonymizes case comment data before it leaves Salesforce. PII and sensitive identifiers are masked so the AI model processes only the content needed to perform the analysis. Results are returned directly to the case record in Salesforce.

The root cause analysis prompt is designed to replace the manual parsing step. Agents no longer need to read every case comment to understand the issue and formulate a troubleshooting path — the AI does that in a single run and presents the findings in a structured format.

The output includes a problem statement based on the case content, a list of potential root causes that commonly lead to that type of issue, and corrective actions the agent can take to resolve the case. This gives the agent a structured starting point rather than a blank screen.

Yes. GPTfy supports Flow-based automation, which means you can configure root cause analysis to run automatically when a case reaches a certain status or when new case comments are added — without requiring any agent action.

Any high-volume support operation benefits — particularly where cases involve technical issues, billing disputes, or multi-step troubleshooting. The demo uses a Service Cloud case, but the same pattern applies to any object with unstructured case comment data.

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Video transcript
So one way AI can boost the productivity of Salesforce users is using its contextual capabilities to conduct a root cause analysis on a service cloud case. So we have this root cause analysis prompt selected, and what it will do is take the information related to this case, like these case comments over here, anonymize it, and then send it over to AI. So we're gonna run it and what it will do is it'll determine the problem that the customer is facing based on the case comments and it will give us potential root causes that commonly lead to this problem, as well as some corrective actions we can take. This way your service cloud end users won't have to parse through case comments individually and manually have to troubleshoot the issue on their own. Now that AI has laid out some potential next steps for us, we can spend less time pondering how to solve it and more time taking the necessary actions to resolve this case.

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Last updated: February 2026