One Sentence. Two Records.
Tell your GPTfy agent you met someone new. It creates the contact, logs the visit, and links both to the right account; no forms, no navigation.
Reps skip CRM updates because logging one new contact means finding the account, creating the contact, filling out an activity form, and linking it all together. This demo shows a rep doing all of it from one plain-English request, inside the Salesforce app they already carry.
Capabilities shown
One Request, Two Records
- Creating a contact and logging an activity are normally two separate jobs in Salesforce; one sentence does both.
- Both records are associated with the right account automatically, with no lookup or navigation by the rep.
Asks Only What It Needs
- The GPTfy agent detects that the person does not exist in Salesforce yet and requests the missing required fields.
- In the demo it asks for two things only: last name and title. Everything else it infers from the request.
Structured Activity, Not Just a Note
- The logged visit carries a written description of what was discussed, not a raw dictation dump.
- Key points and conversation sentiment are captured on the activity record alongside the summary.
Skills: One Job Each
- A skill is one specific job the GPTfy agent can do in the CRM; creating a contact and logging a visit is a single skill among several.
- The rep asks in plain English and the agent selects the right skill, so there is nothing to learn or configure per request.
Use this video when
A field rep who just met a new stakeholder on site logs the person and the visit before leaving the parking lot
An account executive captures a new contact met at a conference without opening a laptop
A rep working an existing account adds a newly introduced decision-maker without hunting for the account record
A sales manager gets a real record of every relationship instead of the handful reps remembered to type up
A team handing an account to a new owner inherits complete contact and activity history rather than gaps
A mobile-first sales org keeps CRM data current in the field, where the conversations actually happen
Frequently asked questions
Yes. That is the scenario shown in this demo. The rep says they met a new person at a customer, and the GPTfy agent recognizes the person is not in Salesforce. It creates the contact under the correct account and logs the visit as a completed activity, treating what would normally be two separate jobs as one request.
Only what the GPTfy agent cannot infer. In the demo the rep says the person's first name, their company, and what was discussed. The agent then asks for two missing details required to create the contact: last name and title. It does not walk the rep through a form or ask for anything it already has.
A written summary of the conversation, the key points discussed, and the sentiment of the interaction. In the demo the activity reads that the rep met with Dave Miller at Rolling Hills Cattle Company and discussed the renewal process, with key points and sentiment captured alongside it.
A skill is one specific job the GPTfy agent knows how to do inside your CRM. Creating a contact and logging a visit is one skill. The agent in this demo also has skills for pulling up accounts, checking open deals, checking open cases, seeing what has happened recently, looking up a contract, and setting a follow-up. The rep asks in plain English and the agent picks the right skill.
No. GPTfy runs inside the Salesforce app reps already carry, so there is no new application to roll out, no second login, and no separate tool for reps to remember. That matters for adoption, because the CRM updates happen where the rep already is.
Dictation produces text that still has to be filed against the right records. Here the GPTfy agent acts on the request: it creates the contact, logs the activity, links both to the correct account, and structures the summary into key points and sentiment. The rep never navigates to a record or fills out a form.
Ready to see this in your Salesforce org?
Book a 45-minute session and we'll walk through this use case using your own data.
Video transcript
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