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GPTfy - Salesforce Native AI Platform

Always-On Support. Any Language. Fully Secured.

GPTfy extends Einstein Chatbot with live Salesforce data access, automatic language detection, and guardrails that prevent out-of-scope answers — around the clock.

This demo shows how GPTfy gives Einstein Chatbot the ability to answer account-specific questions from live Salesforce data in any language, while enforcing security boundaries that prevent the chatbot from answering questions outside its defined scope.

What this demo covers

Live Salesforce Data in the Chatbot

  • GPTfy gives Einstein Chatbot access to account-specific records — fees, transactions, grades, and custom objects.
  • Data is retrieved at query time from Salesforce, not from a static snapshot or knowledge base export.
  • Each session is scoped to the logged-in user's records, ensuring appropriate data boundaries.

Automatic Multilingual Support

  • The chatbot detects the language of each incoming question without any user configuration.
  • GPTfy translates the question to English, queries Salesforce, retrieves the answer, and returns the response in the user's original language.
  • Demonstrated live in this video with French-language queries against an English Salesforce data store.

Security Guardrails and Scoped Access

  • GPTfy enforces a fixed, admin-controlled boundary around what data the chatbot can access and disclose.
  • Questions outside the defined scope are declined rather than answered with uncontrolled AI output.
  • Addresses the top security concern organizations have when evaluating chatbot deployments.

Knowledge Base and Account Queries Together

  • Users can ask general questions from knowledge base articles and account-specific questions in the same session.
  • The chatbot handles follow-up questions naturally, building context across a multi-turn conversation.

Use this video when

A student asks about their course grades, fees paid, and teacher comments — all answered from live Salesforce records without a support agent

A customer service team wants to extend self-service to multilingual users without maintaining separate language-specific chatbot configurations

A service leader needs to demonstrate to security reviewers that the chatbot cannot surface data beyond each user's permitted scope

An organization wants to provide 24/7 account inquiries without scaling the human support team proportionally

A product team needs to show that the chatbot declines out-of-scope questions reliably before going to production

An admin wants to configure which Salesforce objects the chatbot can access without granting AI open-ended access to the entire org

Frequently asked questions

GPTfy sits between Einstein Chatbot and your Salesforce data, giving the chatbot access to live account records — fees, grades, transactions, and other structured data — at any hour without requiring a human agent. This extends Einstein Chatbot beyond general knowledge base responses into account-specific, always-on self-service.

GPTfy automatically detects the language of the incoming question, translates it to English to query the Salesforce data store, retrieves the relevant answer, and returns the response translated back into the user's original language. The demo shows this working with French — the user asks in French and receives a coherent, accurate French-language response.

GPTfy enforces security boundaries around what the chatbot can and cannot answer. When a user asks a question outside the defined scope, the chatbot declines to respond rather than generating an uncontrolled answer. This is a critical protection for production deployments where customers worry about AI systems disclosing information beyond their permitted access.

GPTfy provides limited, contained, and secured access to a fixed set of information within Salesforce rather than granting AI unfettered access to the entire org. The chatbot only surfaces data relevant to the logged-in user's account, ensuring that each session is scoped to the appropriate records and relationships.

Yes. GPTfy supports both modalities in the same conversation. Users can ask general questions that draw on knowledge base articles and account-specific questions that pull from their individual Salesforce records in the same session. The demo shows this in a higher education context — general course questions alongside personal grade and fee inquiries.

Any structured Salesforce data that you configure GPTfy to expose is accessible to the chatbot — including related lists, custom objects, fees, transactions, grades, case history, and account details. The specific data accessible in a given deployment is controlled by your Salesforce admins, keeping exposure aligned to what each user should see.

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Video transcript
So I have a contact and I have a bunch of fees and transactions for this person. I have some grades for this person — for various subjects and things like that. And then CS101 got a grade and there's some comments about it. There is information like this on the right. So if I go here, what I want to do is I want to start asking some questions from it. Let me just ask a generic sort of question first. So I'm just going to ask this question, and the idea is that the chatbot is able to basically answer that question. This is a generic question. You could do some version of that today, where you can answer this question and you can get an answer back. That's good. Interesting. It's just a regular chatbot experience so far. I'm going to now try and ask the same question in a different language. And for those of you who speak French, you can see that I've asked this question in French. And what's happened now is the AI can actually detect that you asked this question in French. It's basically still translating it into English, going against my existing data store, getting the response, translating it into French, and presenting it to you. 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, right — 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