Use Salesforce with an AI Browser for Support Triage

If you use Salesforce and you regularly need to triage and respond to support, the bottleneck is usually the same: Salesforce holds part of the context, but support triage also needs signals that live outside it - on the public web, in LinkedIn, in news, in other connected apps. Strawberry is built to combine the Salesforce context with the rest of the browser, and run the full workflow as a companion you can re-trigger every week.

This page describes specifically how Strawberry handles support triage when Salesforce is one of the inputs. It names the Salesforce surfaces involved, the signals the workflow actually needs, an example prompt you can paste, and what a good output looks like.

The job a support engineer, founder doing support, CS lead is trying to do

The goal of support triage is to categorise inbound tickets, surface the urgent ones, and draft accurate replies grounded in product source-of-truth. The success metric is concrete: first-response time under 2 hours, accurate-categorisation rate above 95%, draft-edits-before-send under 20%. That definition matters because it shapes what Salesforce needs to contribute to the workflow.

What signals support triage actually needs

For each signal below, here is whether Salesforce can contribute directly or whether Strawberry has to find it via the browser:

• Ticket category (billing, bug, feature request, account, security) - Salesforce does not contain this directly. Strawberry uses the browser plus public sources to fetch it.
• Sentiment (positive, neutral, frustrated, churn-risk) - Salesforce does not contain this directly. Strawberry uses the browser plus public sources to fetch it.
• Product state (subscription tier, recent activity, feature flag) - Salesforce does not contain this directly. Strawberry uses the browser plus public sources to fetch it.
• History (has this user reported the same before) - Salesforce does not contain this directly. Strawberry uses the browser plus public sources to fetch it.
• GitHub/Linear status if it's a bug - Salesforce does not contain this directly. Strawberry uses the browser plus public sources to fetch it.
• Team-mate replies already in the thread - Salesforce does not contain this directly. Strawberry uses the browser plus public sources to fetch it.

What Strawberry can do inside Salesforce

Strawberry can read an Account or Opportunity, pull related Contacts and Activities, and combine that context with web research for high-touch deal preparation.

Salesforce surfaces Strawberry uses for this workflow: accounts, opportunities, contacts, leads, reports.

How Strawberry runs support triage with Salesforce

1. Strawberry opens the Salesforce accounts that contains the relevant context.
2. The companion pulls related context from Salesforce (opportunities, history, attached files) where it exists.
3. For the parts Salesforce does not store, Strawberry uses the browser - web search, LinkedIn, news, the prospect's website.
4. Strawberry synthesises the output in the shape this workflow needs: A draft reply per ticket, plus a category label and priority - human reviews before send.
5. A human reviews before any external action (send, update, post). Then the approved output is saved back to Salesforce or your system of record.

Example Strawberry prompt

Paste this in a new Strawberry chat with Salesforce connected. Adjust the specifics to your actual ICP, role, or topic.

Read this Salesforce accounts and any linked context.
Then run a full support triage workflow on it. Use the browser to fill any gaps not in Salesforce.
Return the output in the shape we use for support triage: A draft reply per ticket, plus a category label and priority - human reviews before send.
Do not send anything externally. Save the draft to me to review.

What a good support triage output looks like

Here is what a finished output for support triage should look like in practice. The specifics will change for your use case, but the shape should look similar:

• Ticket #1962 - Marcus Rosenberg (marcus@clubstill.com)
• Category: billing - plan-state mismatch
• Priority: P1 (paying user, $118 charge vs Intern credits)
• Verified: Stripe shows Intern, charge log shows $118 Part-Time amount, credits granted at Intern rate
• Draft reply: confirm Intern is active, apologise for the rate mismatch, grant 22k credit balance to match Part-Time tier for current cycle, no refund promised

Why Salesforce for this, and where to use a different tool

Salesforce is strong for this workflow because Strawberry can read an Account or Opportunity, pull related Contacts and Activities, and combine that context with web research for high-touch deal preparation.

Where Salesforce falls short Salesforce permission model is strict; custom objects and field-level security limit what agents can read; API call limits apply.

Consider also Google Sheets for one-off lists.

Common mistakes when running support triage

• Auto-replying with 'we'll look into it' without doing the work
• Ignoring teammate replies already in the thread
• Guessing about product behaviour instead of checking GitHub or source code
• Automated security-report replies (always a major mistake - escalate to a human only)

Connecting Salesforce to Strawberry

Salesforce OAuth - production access requires Connected App configuration in the user's org. Once connected, the companion can read the surfaces above without re-authenticating, and any write action still requires explicit human approval the first time the workflow runs.

Caveats

Do not let any AI agent send emails, update CRM records, or change shared systems without a clear approval step. Strawberry is strongest when the workflow combines browser context with connected-app context and a human review for sensitive actions.