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GPTfy - Salesforce Native AI Platform

Chatbot Answers. Personalized to Every Account.

GPTfy gives Einstein Chatbot access to individual Salesforce records so every response reflects that specific user's data — with scoped access and guardrails built in.

Generic chatbot responses frustrate users who need account-specific answers. This demo shows how GPTfy connects Einstein Chatbot to individual Salesforce records — courses, grades, fees, and instructor comments — while enforcing security guardrails that prevent the AI from surfacing data it should not.

What this demo covers

Account-Specific Salesforce Data in Every Response

  • GPTfy connects Einstein Chatbot to the logged-in user's Salesforce records at query time.
  • Responses reflect personal data — courses taken, grades earned, fees paid, and instructor comments.
  • The chatbot moves beyond generic knowledge base answers into genuinely personalized self-service.

Multi-Turn Conversations Across Data Types

  • Users can ask follow-up questions that build on earlier answers within the same session.
  • The chatbot maintains context — a question about a specific course follows naturally from a list of courses.
  • Different Salesforce objects (courses, grades, fees) are accessible within a single conversational thread.

Scoped Access with Security Guardrails

  • GPTfy provides limited, admin-defined access to specific Salesforce fields and objects — not the entire org.
  • Each session is scoped to the authenticated user's own records, preventing cross-account data disclosure.
  • Out-of-scope questions are declined at the guardrail layer, not through prompt engineering alone.

Admin-Controlled Configuration

  • Admins define which Salesforce objects and fields the chatbot can access through GPTfy configuration.
  • Changes to accessible data take effect through configuration updates, with no Apex deployment required.

Use this video when

A student asks about their specific course grades and instructor feedback without contacting the registrar's office

A customer wants to review their fee history and payment status through a self-service chatbot at any hour

A service team wants to reduce high-volume, routine data-lookup inquiries without scaling the support headcount

A compliance officer needs to verify that the chatbot cannot surface one user's records in another user's session

An admin wants to add a new Salesforce object to the chatbot's accessible data without writing Apex code

A product team needs to demonstrate that the chatbot declines unauthorized questions reliably before go-live

Frequently asked questions

GPTfy connects Einstein Chatbot to the logged-in user's Salesforce records, allowing the chatbot to answer questions about their specific account — not just generic knowledge base content. When a user asks about their courses, grades, fees, or transaction history, GPTfy retrieves the relevant records from Salesforce and surfaces them through the chatbot in a conversational format.

The chatbot can answer questions about any Salesforce data configured for access — in this demo, that includes courses taken, grades received, instructor comments on specific courses, and fee history. The same pattern applies to other industries: a financial services chatbot could surface account balances and transaction history, while a healthcare chatbot could surface appointment and care plan information.

GPTfy maintains conversational context across multiple questions in the same session. A user can ask about their course list, then drill into grades for a specific course, then ask about instructor comments for that course — and the chatbot answers each follow-up with the appropriate Salesforce data without losing context from earlier in the conversation.

GPTfy enforces a fixed, admin-defined boundary around what Salesforce data the chatbot can surface. The chatbot has limited, contained, secured access to a specific set of fields and objects — not open-ended access to the entire Salesforce org. When a user asks a question outside that boundary, the chatbot declines to answer, preventing unauthorized data disclosure.

Yes. GPTfy scopes each chatbot session to the records associated with the authenticated Salesforce user. A student only sees their own grades and fees, not another student's records. This user-level scoping is enforced by GPTfy's security layer, not by the AI model itself, making it a reliable control rather than a prompt-based suggestion.

Enabling GPTfy-powered personalization in Einstein Chatbot requires configuring which Salesforce objects and fields GPTfy can access, then connecting the GPTfy agent to your Einstein Chatbot deployment. No custom Apex development is required. Admins control the data scope through configuration, and changes to accessible data are applied without code deployments.

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Book a 45-minute session and we'll walk through this use case using your own data.

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Video transcript
So my next question is really trying to figure out if I can get answers from it which are specific to my account. And let's see if that works. So as you can see, this is now starting to pull information about my particular account — about this person. Mark Johnson was logged in. It's looking at some of the courses Mark has taken and you're starting to see them. There were five courses that Mark took. And you can see that now if I ask more questions, I can ask for more details. I want to say — what were my grades in these respective courses? So it knows these five courses I took, and is now telling me what grades I have in those courses. And for a particular course I'm going to ask about course comments — are there any comments that my teacher had put for this particular course? And what you start to see is that it is pulling information from my Salesforce, and this is done very securely because we have GPTfy between. So it is not like unfettered access to my Salesforce environment. It's not that we have given AI access to everything. It is a very limited, contained, secured access to a very fixed set of information that we are providing. So I can continue to ask more questions. I can ask about my fees — how much I paid — all of that. And what you're starting to see is that this chatbot is able to answer questions in a lot of depth about things that it knows about what I have done so far. So it's giving me the fees I paid and these other grades I'm getting. A lot of information very relevant to what we're trying to do. Again, the idea is that you are able to ask questions back and forth based on knowledge base articles or based on the account information. I'm going to ask a question that it's not supposed to answer. And the idea is that there are enough guardrails and security around it so that it doesn't answer these kinds of questions. This is a pretty significant risk that a lot of customers think about when they are looking at chatbots.

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Last updated: February 2026