---
title: "Introducing Rippit + Granola"
description: "Rippit's Granola integration syncs meeting notes and transcripts to analyze alongside support conversations, then turns the work into a recurring agent."
canonical: https://www.rippit.com/news/rippit-granola-integration
type: Company News
datePublished: 2026-09-30
---

# Introducing Rippit + Granola

Bring meeting notes and transcripts into Rippit. Analyze them alongside customer support conversations to see whether the decisions your team makes hold up with customers—and put an agent to work keeping the two connected.

By Vasu Prathipati, CEO of Rippit · Published September 30, 2026

**Rippit's Granola integration brings your Granola meetings into Rippit's Growth Data Platform.** It syncs AI summaries, private notes, transcripts and meeting context on a schedule, read-only. Rippit analyzes them alongside your support conversations, saves what it finds as structured fields, and runs agents that send findings with their evidence to Slack or email. Use it to check what your team decided in meetings against what customers report afterward. A separate Granola MCP connection lets Rippit's agent read meetings directly in Granola during an investigation.

In Monday's product meeting, your team decides an onboarding problem is an edge case. Over the next week, another twenty customers contacted support about it.

In an engineering review, you discuss a fix. After it ships, customers keep reporting the same issue.

In a leadership meeting, you make simplifying setup a priority. A month later, you want to know whether customers are finding it easier.

Your meetings capture decisions, assumptions, and commitments. Customer conversations provide evidence of how those decisions play out.

That gap is where companies lose ground unnoticed: meetings and support sit in different tools, so a decision built on a disproved assumption can stand for a quarter. Reading one against the other lets your team catch a wrong call while it's still easy to change.

Today, we're introducing Rippit's Granola integration: sync meeting notes and transcripts, analyze them alongside Zendesk and Intercom conversations, save the findings as structured data, and turn the analysis into an agent that delivers to Slack or email on a schedule.

**Internal context**

Granola meeting notes and decisions

Read-only

**Customer evidence**

Helpdesk tickets, calls, chats and email

**Rippit**

Classifies conversations, compares them with meeting decisions, and measures what changes

An agent runs on a schedule and sends a brief with evidence links to Slack

*How it fits together: Granola supplies what your team decided, customer conversations supply what customers report, and Rippit connects the two on a schedule.*

## Why add Rippit if you already use Granola?

Granola helps you capture meetings and make use of what was discussed. Rippit brings those meetings into a broader analytical workflow across your conversation data.

| What Rippit adds | Why it matters |
| --- | --- |
| Broader conversation coverage | Analyze synced Granola meetings next to Zendesk tickets and Intercom conversations. |
| Structured, reusable analysis | Classify conversations into saved columns, then calculate counts, percentages, and breakdowns you can filter, chart, and revisit. |
| Managed recurring work | Turn the analysis into an agent with a defined data scope, output, delivery destination, and schedule. |

For example, start with what your team decided about onboarding. Then investigate how often the underlying problems appear in customer conversations, which workarounds succeed, and whether the situation improves after a change.

## Bring Granola meetings into your analysis

Rippit's [Granola data integration](https://docs.rippit.com/plg/data-integrations/granola) imports meeting content on a schedule. Each synced Granola note becomes a conversation in Rippit, containing:

- **The AI summary** from Granola
- **Private notes**, when present, stored as a separate internal comment
- **The full available transcript**, organized into speaker turns
- **Meeting context**, including the title, owner, attendees, folders, and a link to the original Granola note

That gives you a dataset you can analyze repeatedly. You can investigate what was said across the synced meetings, save classifications, and compare those findings with customer support data already in Rippit.

## Start with a question that needs both sources

Imagine your product team has just reviewed next quarter's roadmap. The priorities and reasoning are captured in Granola. Meanwhile, thousands of support conversations describe the problems customers encounter every day.

You want to know:

"Compare the priorities discussed in our synced product-planning meetings with the issues customers raised in support last month. Which problems are we addressing, and where should we take another look?"

Here is how the workflow comes together.

### 1. Read the decision and the customer evidence

The meeting might explain why your team deferred an onboarding improvement: the problem appeared uncommon, a workaround seemed sufficient, or another issue was more urgent.

The support conversations let you examine those assumptions. Are customers using the workaround successfully? Is the issue becoming more frequent? Are they describing a different problem from the one discussed internally?

With meeting transcripts available in Rippit, you can investigate the discussion behind a decision as well as its summary. Source links let your team return to the original Granola note.

### 2. Turn conversations into reusable analysis

Ask Rippit to add the classifications your question needs. For an onboarding investigation, those might include:

- The problem discussed in each conversation.
- The onboarding step involved.
- Whether a workaround resolved the issue.
- Any commitment or proposed fix mentioned.
- The severity and supporting evidence.

Rippit can apply classifications across the records in your analysis (up to 10,000 rows in a worksheet) and save the results in structured columns; a scheduled agent applies them to new records on each run. Then calculate how often each issue appears, compare periods, and break the findings down by relevant fields.

The analysis remains available for follow-up questions, reports, and charts. You can reuse the classifications or add new ones as the investigation develops.

### 3. Make the investigation a standing job

Once the analysis is useful, turn it into an [agent](https://docs.rippit.com/pipelines/overview).

For example:

**Agent prompt**

"Every Friday, analyze this week's onboarding support conversations alongside our synced product and engineering meetings from the past 30 days. Highlight growing issues, reports related to documented fixes, and recurring complaints with no matching discussion in the meetings checked. Send a brief with evidence links to the product Slack channel. If nothing needs attention, send a short update saying 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 flow, review the evidence, and activate it. Scheduled runs bring fresh feedback back without anyone having to ask. Tests can send real messages, so use yourself or a test channel as the delivery destination while refining the agent.

## Agents that scan, analyze and deliver

The same approach supports several recurring jobs:

| Custom agent | Scan | Analyze | Deliver |
| --- | --- | --- | --- |
| A custom priority-alignment agent | Synced planning meetings and customer support conversations | Compare stated priorities with recurring customer problems | Send a weekly brief with evidence and questions for the next planning meeting |
| A custom fix-follow-through agent | Meeting discussions of fixes and subsequent support reports | Identify problems still being reported after a confirmed release date | Send examples for the team to investigate |
| A custom commitment-alignment agent | Synced internal meetings where the team agreed what to do for customers, and related support conversations | Check whether what the team agreed internally is reflected in what customers report afterward, and flag issues still unresolved | Deliver a follow-up brief to the account team |
| A custom decision-review agent | Leadership and planning meetings where a priority was set, and the support conversations since | Check whether customer evidence still supports the assumptions behind each decision | Send leadership a monthly brief with the evidence for and against |

These are examples of agents you can build, not packaged agents. To turn support conversations into evidence for the roadmap, see [How to Mine Product Feedback From Support Tickets and Call Transcripts](https://www.rippit.com/playbooks/mine-product-feedback-from-support-tickets-and-calls).

## Two ways to connect Granola

Rippit supports both a data integration and a Granola MCP connection. Choose the connection that fits the work, or use both.

|  | Granola data integration | Granola MCP connection |
| --- | --- | --- |
| Purpose | Sync meeting content into Rippit for analysis, reporting, and agents | Let Rippit's agent search and read meeting content directly in Granola during an investigation |
| Setup | A Granola API key, available on Business or Enterprise; a Rippit workspace admin sets up the integration | Browser sign-in to Granola; a Rippit workspace admin creates the connection |
| Data access | Imports accessible notes, summaries, private notes, and transcripts; first sync backfills all history by default | Reads content available to the signed-in user through Granola MCP, subject to plan and admin settings |
| Updates | New and edited notes sync on a schedule | The agent fetches content when it uses the enabled tools |
| Changes to Granola | Read-only | Read-only |

For the MCP connection, transcript access requires a paid Granola plan. On Granola Enterprise, an admin must enable MCP access. An MCP connection used by an agent must be shared organization-wide; its users access the connecting account's available meeting content.

For the data integration, review the authorizing account's access before connecting: private notes are included in the imported content. Disconnecting stops future syncs but does not remove data already imported, and the Granola API key remains valid until revoked in Granola.

See the [data integration guide](https://docs.rippit.com/plg/data-integrations/granola) and the [MCP connection guide](https://docs.rippit.com/agentic-chat/connectors/granola) for setup and access details.

## Get started

Have a Rippit workspace admin connect Granola with an API key from your Granola Business or Enterprise plan. Once your meetings have synced, start with one decision you want to evaluate:

"What did we decide about onboarding in our synced meetings, and what are customers reporting about it in support now?"

Review the evidence, refine the classifications, and turn the version you trust into an agent.

Your team keeps making decisions. Your customers keep giving you feedback. Put an agent to work connecting the two.

[Try Rippit free](https://app.rippit.com/signup) [or request demo](https://www.rippit.com/request-demo)

## FAQ

### What does Rippit's Granola integration sync?

Each synced Granola note becomes a conversation in Rippit with the AI summary, any private notes (stored as a separate internal comment), the full available transcript in speaker turns, and meeting context: title, owner, attendees, folders and a link to the original note. New and edited notes sync on a schedule, with an initial backfill of all history by default.

### What's the difference between the Granola data integration and the Granola MCP connection?

The data integration syncs meeting content into Rippit for analysis, reporting and agents. The MCP connection lets Rippit's agent search and read meetings directly in Granola during an investigation. Both are read-only, and you can use either or both.

### Which Granola plan do I need?

The data integration needs a Granola API key, available on Business or Enterprise, and a Rippit workspace admin to set it up. For the MCP connection, transcript access requires a paid Granola plan, and on Granola Enterprise an admin must enable MCP access.

### Are private Granola notes included?

Yes. The data integration includes private notes in the imported content, so review the authorizing account's access before connecting. Disconnecting stops future syncs but doesn't remove data already imported, and the API key stays valid until it's revoked in Granola.

**Documentation reviewed October 1, 2026**

- [Granola data integration](https://docs.rippit.com/plg/data-integrations/granola)
- [How data integrations work](https://docs.rippit.com/plg/data-integrations)
- [Supported integrations](https://docs.rippit.com/plg/supported-integrations)
- [Ask Rippit questions](https://docs.rippit.com/plg/chat/asking-questions)
- [Agents](https://docs.rippit.com/pipelines/overview)
- [Granola MCP connection](https://docs.rippit.com/agentic-chat/connectors/granola)
- [How MCP servers work](https://docs.rippit.com/agentic-chat/overview)
- [Rippit MCP server](https://docs.rippit.com/mcp-server/overview)

## Getting started from an AI agent

There are two ways to connect. Either works.

- MCP server: `https://mcp.rippit.com/mcp` (Streamable HTTP, OAuth). The person signs in or signs up in the browser that opens. No client ID, secret or API key is needed.
- CLI: install with `curl -fsSL https://rippit.sh | sh` or `brew install adtribute/tap/rippit`, then get an account one of two ways:
  - `rippit login`: the person signs in or signs up in a browser.
  - `rippit start`: creates a temporary account with no email or browser, for a person with no Rippit account. `rippit claim --wait` lets them keep it; an unclaimed account is deleted after 14 days.

Then bring in data: connect a provider such as Zendesk, Intercom, Gong or Salesforce, or upload a CSV.

Full steps: https://www.rippit.com/setup.md