Salesforce Agent for Customer Service: total smart automation

In many Customer Service environments, customer requests still arrive through heterogeneous and poorly structured channels, such as certified email (PEC) or shared inboxes. For utilities, banks and insurance companies, telcos, and public administrations, the ability to deliver effective and timely responses is now a decisive factor: it directly impacts service quality, customer satisfaction, and ultimately revenue.

Thanks to a properly configured Salesforce Agent based on Artificial Intelligence, it is possible to automate the entire request management lifecycle: from capturing the incoming communication to proposing a solution, all the way through ticket closure—either with operator support or fully autonomously.

The result is a more accurate, timely, and effective Customer Service, capable of combining operational speed with high-quality responses.

An AI solution for the entire Customer Service lifecycle

Taking a typical Customer Service use case as a reference, the Salesforce Agent application is embedded within a customer support process that begins with the receipt of a certified email (PEC).

The system:

• receives certified emails (PEC) forwarded from the institutional mailbox;
• enables an Artificial Intelligence–based Intelligent Document Processing (IDP) tool to analyze documents and content;
• automatically generates a ticket in Salesforce, linking the sender, content, attachments, and metadata;
• activates the Salesforce Agent, which leverages Artificial Intelligence to suggest or directly execute the next actions.

This Artificial Intelligence–driven Customer Service automation model is easily adaptable across multiple industries—from utilities to banking and insurance, from public administrations to telcos and retail—in all contexts where email and certified email (PEC) represent a primary channel for interacting with customers and citizens.

Simple requests: Salesforce Agent and AI for full automation

When the system recognizes that the customer request is a simple informational query (FAQs, case status, contract terms, downloadable documentation), the Salesforce Agent steps in by leveraging Artificial Intelligence to:

• analyze and identify the intent of the request;
• autonomously prepare the most appropriate text response, based on corporate information sources (knowledge base, internal documentation, policies).

The process can follow two variants:

• Human-in-the-loop: the Salesforce Agent proposes a draft response to the operator, who can review, edit, and approve it. Once validated, the communication is sent to the customer and the case is automatically closed in Salesforce.
• Fully automated: when the confidence level and risk profile allow it, the Salesforce Agent sends the response directly to the customer and closes the case without human intervention.

In both approaches, the use of Artificial Intelligence in Customer Service enables faster response times, a significant reduction in manual work, and greater consistency in customer communications.

Complex requests: AI supporting the operator

When a request is complex, ambiguous, or high-impact—such as complaints, disputes, or technically complex cases—the process remains under the responsibility of the human operator. In these situations, the Salesforce Agent plays an advanced support role.

The workflow предусматриes that:

• the ticket is created in Salesforce with all contextual information extracted from the certified email (PEC) and its attachments;
• the Salesforce Agent, through conversational AI, suggests a possible solution or a set of next steps;
• the operator can interact with the agent to obtain clarifications, summaries, related documents, or references to regulations, internal procedures, and response templates.

The platform user always has the final say, with the ability to accept, modify, or reject the agent’s suggestions before responding to the customer and closing the case.

This hybrid model enhances the role of Artificial Intelligence in Customer Service as a tool for support, training, and continuous improvement, while preserving human control in sensitive cases.

Key element: the "proposed solution" field

In all the scenarios described, the Salesforce Agent populates a dedicated case field with a suggested solution. This element is strategic because it:

• provides the operator with an immediate starting point, reducing analysis time;
• enables tracking, for audit and continuous improvement purposes, of the agent’s suggestions compared to final decisions;
• allows the creation of reports and KPIs to measure the effectiveness of Artificial Intelligence in Customer Service;
• facilitates model training and retraining by highlighting knowledge gaps and areas for improvement.

In practice, the “proposed solution” field represents the point of contact between AI and human expertise: it speeds up operators’ work and makes the contribution of the Salesforce Agent measurable. This balance is exactly what the Mashfrog experience is built on—shaped through complex Customer Service projects where governance, measurability, and the adoption of Artificial Intelligence are key factors in generating real and sustainable value.

Tangible benefits across all industries

Implementing an Artificial Intelligence–based Salesforce Agent delivers cross-industry benefits, regardless of sector:

• shorter handling times for simple requests;
• greater operator efficiency, allowing teams to focus on more complex cases;
• more consistent, higher-quality responses;
• a Customer Service that is easier to monitor, measure, and govern.

Automating Customer Service does not mean losing control, but gaining speed, quality, and traceability. A well-designed Salesforce Agent integrates Artificial Intelligence with human expertise, adapting to any industry and level of complexity.

If the goal is to turn customer requests into an efficient and measurable process, now is the right time to design a tailored solution. Let’s talk.