Introducing Rippit + Fireflies

Why add Rippit if you already use Fireflies?

Fireflies captures valuable meeting context: what people discussed, the questions they raised, and the actions they agreed to take. Rippit brings that context into a broader analytical workflow across your conversation data. For a side-by-side look, see Rippit vs. Fireflies.

For example, start with the difficulties customers describe in onboarding calls. Investigate how often those same problems appear in support, which workarounds seem to help, and whether the complaints become less common after a change.

The meeting gives you the detail. The broader dataset helps you understand how widespread the problem is.

Bring Fireflies meetings into your analysis

Rippit’s Fireflies integration imports meeting transcripts and AI summaries on a schedule. Each synced meeting becomes a conversation in Rippit, containing:

• The transcript: Organized into timestamped speaker turns, using the speaker names identified by Fireflies.
• The meeting summary: Fireflies’ AI overview, notes, and action items.
• Meeting context: Title, organizer, attendee emails, duration, and keywords.
• The source link: A link back to the meeting in Fireflies.

That gives your team both a summary to orient the investigation and the underlying discussion to examine more closely.

A summary might say a customer needs help with reporting. The transcript can reveal what they were trying to accomplish, why the current approach failed, and what they expected instead.

Start with a question that needs more than meeting notes

Imagine your customer success team has finished a month of onboarding calls. Fireflies captured the discussions, including questions, concerns, and proposed workarounds.

Meanwhile, your support conversations contain more examples of customers working through the same setup process.

You want to know:

“Compare the onboarding problems discussed in our synced Fireflies customer meetings with the issues raised in support over the past 30 days. Which obstacles appear across both, and what should we investigate first?”

Here is how the workflow comes together.

1. Read what customers are trying to accomplish

Start with the customer’s goal.

Someone asking how to export a report might really need to share results with their leadership team. Someone struggling to connect a data source might be blocked from completing their first workflow.

Rippit can examine the meeting transcript to identify those underlying needs, then look for similar themes in your connected support data.

Are customers describing the same obstacle in different words? Does a workaround discussed on calls also appear in support? Are customers reporting that it helps, or that they are still stuck?

Comparing themes across sources helps your team distinguish an isolated question from a recurring source of friction.

2. Turn the findings into reusable analysis

Ask Rippit to classify the selected conversations using the distinctions your team needs. For an onboarding investigation, those might include:

• The customer’s intended outcome.
• The setup step or feature involved.
• The obstacle they described.
• The workaround or next step discussed.
• Whether the customer confirmed the problem was resolved.
• The supporting evidence.

Save those classifications as structured columns. Then calculate how often each issue appears, compare meeting and support themes, and examine changes over time.

Keep proposed actions separate from confirmed outcomes. A meeting’s action item tells you what someone planned to do; later customer feedback may help establish whether it worked.

The analysis stays available for follow-up questions, reports, and charts. Your team can refine the categories as it learns more.

3. Make the investigation a standing job

Once the analysis is useful, turn it into an Agent App.

For example:

“Every Friday morning, analyze this week’s onboarding support conversations alongside our synced Fireflies customer onboarding meetings from the past 30 days. Highlight recurring obstacles, workarounds customers say helped, and issues that still appear unresolved. Send a brief with evidence links to the customer success Slack channel. If nothing significant has changed, say so.”

Rippit builds a flow you can inspect and adjust: which records it reads, what it analyzes, how it formats the findings, where it sends them, and when it runs.

Test the findings, refine the instructions, then define who should receive the ongoing analysis, how (email or Slack), or what destinations to write results to via MCP or direct integrations. Activate the app to begin the workflow.

Fresh conversations then become part of an ongoing investigation, without someone having to remember to ask the same question each week.

Agents that scan, analyze, and act

The same approach supports several recurring jobs:

Connect Fireflies to Rippit

A Rippit workspace admin can set up the integration using a Fireflies API key and a workspace name.

Create the key in Fireflies under Settings → Developer Settings. The workspace name labels the connection in Rippit.

Meetings without transcript text are skipped. Rippit rechecks the previous 24 hours daily to pick up transcripts that finish processing later.

Syncing follows the meeting date rather than its last edit, so changes to older meetings are not continuously refreshed. Fireflies API limits also vary by plan; larger backfills or busy days can exhaust the daily quota on Free or Pro.

See the Fireflies integration documentation for setup, access, and sync details.

Get started

Connect Fireflies, let your meetings sync, and start with one question your team wants to understand:

“What problems keep coming up in our customer meetings, and how often do we see the same issues in support?”

Review the evidence. Save the classifications that make the patterns clearer. Then turn the investigation into an Agent App that keeps checking.

Your customers keep telling you what could be better. Put their conversations to work together.