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            <title>
									Fireflies.ai Reviews - Welcome to Stackinsight community. Join the discussion about products and tools for work Forum				            </title>
            <link>https://communities.stackinsight.net/community/aitr-fireflies-ai/</link>
            <description>Welcome to Stackinsight community. Join the discussion about products and tools for work Discussion Board</description>
            <language>en-US</language>
            <lastBuildDate>Fri, 02 Oct 2026 09:09:26 +0000</lastBuildDate>
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							                    <item>
                        <title>Why is Fireflies.ai so inaccurate with industry-specific acronyms?</title>
                        <link>https://communities.stackinsight.net/community/aitr-fireflies-ai/why-is-fireflies-ai-so-inaccurate-with-industry-specific-acronyms-2/</link>
                        <pubDate>Mon, 28 Sep 2026 18:25:58 +0000</pubDate>
                        <description><![CDATA[We&#039;re evaluating Fireflies.ai for post-incident meeting transcription. The accuracy on general conversation is acceptable, but it consistently mangles critical SRE and infrastructure acronym...]]></description>
                        <content:encoded><![CDATA[We're evaluating Fireflies.ai for post-incident meeting transcription. The accuracy on general conversation is acceptable, but it consistently mangles critical SRE and infrastructure acronyms.

Examples from last week's bridge:
* It transcribed "MTTR" as "matter" or "empty are".
* "P99 latency" became "p ninety nine latency" (okay) but also once as "pine tree ninety latency".
* "SEV-2" was written as "seven two".

This creates extra work for postmortem documentation and risks miscommunication. The tool seems to lack a configurable glossary or the ability to learn from corrections.

Has anyone built a reliable workaround? Or is this a fundamental limitation of their NLP model for technical fields?

—D]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/aitr-fireflies-ai/">Fireflies.ai Reviews</category>                        <dc:creator>dianar</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/aitr-fireflies-ai/why-is-fireflies-ai-so-inaccurate-with-industry-specific-acronyms-2/</guid>
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                        <title>Switched from Fireflies to a DIY Whisper API setup. More work, but full control and cheaper.</title>
                        <link>https://communities.stackinsight.net/community/aitr-fireflies-ai/switched-from-fireflies-to-a-diy-whisper-api-setup-more-work-but-full-control-and-cheaper-2/</link>
                        <pubDate>Sat, 26 Sep 2026 19:51:03 +0000</pubDate>
                        <description><![CDATA[Just wanted to share my recent experiment. After using Fireflies.ai for about 8 months to transcribe my team&#039;s meetings, I finally hit a cost and control wall. It&#039;s a great product, especial...]]></description>
                        <content:encoded><![CDATA[Just wanted to share my recent experiment. After using Fireflies.ai for about 8 months to transcribe my team's meetings, I finally hit a cost and control wall. It's a great product, especially for a quick, all-in-one solution, but I needed more flexibility.

So, I built a DIY pipeline using OpenAI's Whisper API. It's definitely more hands-on, but for my specific use case, it's been a game-changer. Here’s a quick side-by-side of my experience:

**The DIY Setup (Whisper API + My Own Stack):**
*   **Cost:** Roughly 1/3 of what I was paying Fireflies for the same volume. Pay-per-minute is just cheaper at scale.
*   **Control:** I own the data pipeline end-to-end. Audio files go to my cloud storage, transcripts are structured my way, and I can feed them directly into my existing analytics dashboard.
*   **Flexibility:** I can use different Whisper models (like `whisper-1` for speed vs. turbo for cost) depending on the meeting's importance. I also added a step to auto-tag sections based on keywords, which Fireflies couldn't do.
*   **The "Work" Part:** I had to stitch together the recording export, the API calls, and the storage. No nice UI. Error handling is on me. No automatic speaker diarization (I'm using a separate, simpler model for that, which is good enough).

**What I Miss from Fireflies:**
*   The seamless integration with Zoom/Teams calendar was killer. I now have a semi-automated Zapier flow, but it's not as smooth.
*   The out-of-the-box searchable conversation repository was very user-friendly for the team.
*   The AI summaries, while sometimes generic, were a good starting point.

For now, the trade-off is worth it. The cost savings and the ability to tailor the output for my CRO work—like directly linking transcript segments to session replays or A/B test variants—is huge. If you're comfortable with a bit of tinkering and have specific data needs, it's a path worth exploring.

Has anyone else gone down a similar road? Curious if you've found clever ways to handle speaker tracking or integrated transcripts with heatmap tools.

&#x270c;&#xfe0f;]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/aitr-fireflies-ai/">Fireflies.ai Reviews</category>                        <dc:creator>chrisp</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/aitr-fireflies-ai/switched-from-fireflies-to-a-diy-whisper-api-setup-more-work-but-full-control-and-cheaper-2/</guid>
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                        <title>Breaking: Fireflies just announced direct integration with Salesforce. Early access reviews?</title>
                        <link>https://communities.stackinsight.net/community/aitr-fireflies-ai/breaking-fireflies-just-announced-direct-integration-with-salesforce-early-access-reviews-2/</link>
                        <pubDate>Sat, 26 Sep 2026 07:40:56 +0000</pubDate>
                        <description><![CDATA[Just saw the announcement in their newsletter. Fireflies.ai now has a direct Salesforce integration in early access. This could be a game-changer for syncing call notes, action items, and re...]]></description>
                        <content:encoded><![CDATA[Just saw the announcement in their newsletter. Fireflies.ai now has a direct Salesforce integration in early access. This could be a game-changer for syncing call notes, action items, and revenue intelligence directly to Leads, Contacts, or Opportunities.

Has anyone in the community gotten early access yet? I'm especially keen to hear:
- How seamless is the field mapping? Can you push custom keywords/topics?
- Does it create timeline events or just notes in the Activity feed?
- Any impact on Salesforce data storage limits with long transcripts?

Trying to decide if this replaces our current Zapier workflow. The native sync could be much cleaner for the sales team.]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/aitr-fireflies-ai/">Fireflies.ai Reviews</category>                        <dc:creator>adamk</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/aitr-fireflies-ai/breaking-fireflies-just-announced-direct-integration-with-salesforce-early-access-reviews-2/</guid>
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                        <title>Why is Fireflies missing speaker labels so often? Workarounds?</title>
                        <link>https://communities.stackinsight.net/community/aitr-fireflies-ai/why-is-fireflies-missing-speaker-labels-so-often-workarounds-2/</link>
                        <pubDate>Fri, 25 Sep 2026 03:55:48 +0000</pubDate>
                        <description><![CDATA[Just tried Fireflies on a 5-person technical sync. The transcript was decent, but it kept merging three different engineers into one &quot;Speaker 2&quot; label &#x1f605;. My post-meeting cost allocat...]]></description>
                        <content:encoded><![CDATA[Just tried Fireflies on a 5-person technical sync. The transcript was decent, but it kept merging three different engineers into one "Speaker 2" label &#x1f605;. My post-meeting cost allocation idea went out the window.

Happens a lot with remote calls where voices sound similar or people talk fast. Anyone else hitting this?

I need reliable speaker separation for my FinOps reports. What's the best workaround?

*   Manually editing the transcript post-call? (Time-costly!)
*   A specific recording setup (individual audio tracks?) before feeding it to Fireflies?
*   Or another tool that handles this better and integrates with Slack?

Found a semi-workaround for Zoom meetings: record separate audio tracks in Zoom, then upload. Helps a bit, but it's an extra step.

Would love to hear your hacks. My tagging/tracking system depends on it.

#savings]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/aitr-fireflies-ai/">Fireflies.ai Reviews</category>                        <dc:creator>cloud_cost_owen</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/aitr-fireflies-ai/why-is-fireflies-missing-speaker-labels-so-often-workarounds-2/</guid>
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                        <title>How-to: Setting up separate &#039;Notebooks&#039; for each client project to keep things organized.</title>
                        <link>https://communities.stackinsight.net/community/aitr-fireflies-ai/how-to-setting-up-separate-notebooks-for-each-client-project-to-keep-things-organized-2/</link>
                        <pubDate>Mon, 24 Aug 2026 21:35:58 +0000</pubDate>
                        <description><![CDATA[Organizing client work within a single Fireflies.ai account presents a common challenge: transcription sprawl. Without deliberate structure, meetings from different projects become intermixe...]]></description>
                        <content:encoded><![CDATA[Organizing client work within a single Fireflies.ai account presents a common challenge: transcription sprawl. Without deliberate structure, meetings from different projects become intermixed in the main Notebook, making retrieval inefficient and creating potential confidentiality concerns. The platform's Notebooks feature is the logical tool for segmentation, but its implementation requires a systematic approach.

The core strategy is to treat each client project as a distinct operational unit. For every new client engagement, you should create a dedicated Notebook *before* the first meeting is recorded. This ensures all related transcripts, action items, and audio files are isolated from inception. The process is straightforward:

1.  Navigate to the Notebooks section in your Fireflies.ai dashboard.
2.  Click "New Notebook" and name it using a consistent convention (e.g., `Client-Project-YYYY` or `Internal-ProjectName`).
3.  For team accounts, manage member access at this point, inviting only relevant team members to the client-specific Notebook.

The real optimization, however, lies in automation and workflow. You must configure your meeting scheduler and Fireflies bot to direct recordings to the correct Notebook automatically.

*   **Calendar Integration:** In your Fireflies settings, connect your calendar (Google or Outlook). The bot will scan meeting titles and invites.
*   **Notebook Keywords:** Within each Notebook's settings, you can define specific keywords, email addresses, or domains. When the Fireflies bot joins a meeting containing these identifiers, the recording is automatically filed into the corresponding Notebook.
*   **Manual Fallback:** For ad-hoc meetings, you can move recordings post-facto via the "Move to Notebook" option in the transcript's settings menu.

A disciplined naming convention for your Notebooks is critical for scalability. I recommend including the client name, project code, and year. This mirrors cost allocation tags (like AWS resource tags) in cloud infrastructure, allowing for clear attribution. Furthermore, periodically audit Notebook membership to ensure access permissions remain correct, analogous to reviewing IAM policies. This method transforms Fireflies from a simple transcript repository into a structured, client-isolated knowledge base.]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/aitr-fireflies-ai/">Fireflies.ai Reviews</category>                        <dc:creator>cloud_cost_breaker</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/aitr-fireflies-ai/how-to-setting-up-separate-notebooks-for-each-client-project-to-keep-things-organized-2/</guid>
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                        <title>What&#039;s the best way to share transcripts with clients without giving them full account access?</title>
                        <link>https://communities.stackinsight.net/community/aitr-fireflies-ai/whats-the-best-way-to-share-transcripts-with-clients-without-giving-them-full-account-access-2/</link>
                        <pubDate>Sun, 23 Aug 2026 10:00:55 +0000</pubDate>
                        <description><![CDATA[Just got asked by a PM if they could just &quot;hook the client&#039;s email into our Fireflies workspace&quot; so they can see meeting transcripts. Had to shut that down hard. &#x1f6ab; Not giving externa...]]></description>
                        <content:encoded><![CDATA[Just got asked by a PM if they could just "hook the client's email into our Fireflies workspace" so they can see meeting transcripts. Had to shut that down hard. &#x1f6ab; Not giving external clients access to our internal tooling and notes, that's a compliance nightmare waiting to happen.

So, the actual problem: we're using Fireflies.ai to record and transcribe customer calls (mostly for accuracy, CYA, and async handoffs). The sales and support teams want to share *specific* transcripts with the clients, but **not** give them a seat/license or, worse, a login to our account.

The obvious "Share transcript" link from Fireflies is... fine. But it's just a web page. I'm thinking we need something a bit more controlled and maybe automated. My current duct-tape solution is a Python script that uses the API to fetch the transcript and then generates a PDF we can email. It's janky.

Wanted to poll the trenches. What's your stack for this?

*   Are you using the native share features and calling it a day?
*   Built a small portal that serves authenticated, ephemeral links?
*   Just dumping the .txt file into a shared, client-specific S3 bucket with a pre-signed URL?
*   Found a way to lock down the Fireflies shared link with a password or expiry?

My requirements are basically:
- No client accounts on our SaaS tools.
- Transcripts should be read-only, obviously.
- Ideally, links expire or access can be revoked.
- Minimal manual steps for the teams.

Pager duty survivor.]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/aitr-fireflies-ai/">Fireflies.ai Reviews</category>                        <dc:creator>devops_shift_worker</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/aitr-fireflies-ai/whats-the-best-way-to-share-transcripts-with-clients-without-giving-them-full-account-access-2/</guid>
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                        <title>Anyone running Fireflies on a heavy Zoom schedule? Performance issues?</title>
                        <link>https://communities.stackinsight.net/community/aitr-fireflies-ai/anyone-running-fireflies-on-a-heavy-zoom-schedule-performance-issues-2/</link>
                        <pubDate>Sat, 22 Aug 2026 09:05:55 +0000</pubDate>
                        <description><![CDATA[I’ve been roped into evaluating Fireflies.ai for our team’s daily standups and client calls, all hosted on Zoom. We’re talking 8-10 meetings a day, sometimes back-to-back, each running 30-60...]]></description>
                        <content:encoded><![CDATA[I’ve been roped into evaluating Fireflies.ai for our team’s daily standups and client calls, all hosted on Zoom. We’re talking 8-10 meetings a day, sometimes back-to-back, each running 30-60 minutes. The promise of automated transcripts and summaries sounded great in theory, but the reality has been… less than stellar.

The performance under this load is inconsistent at best. The latency between meeting end and transcript availability is wildly unpredictable—sometimes 10 minutes, sometimes over an hour. I’ve seen the bot occasionally drop from calls entirely around the 45-minute mark, leaving the last quarter of a discussion unrecorded. Support’s answer was essentially “network variability,” which is a charmingly vague non-answer when you’re on a stable enterprise connection.

What’s the actual resource footprint on their end? If I were to run something like this myself, I’d want to see clear metrics and scaling logic. Instead, we get a black box that chokes under a perfectly normal meeting cadence.

Has anyone else pushed it with a heavy Zoom schedule and found a workaround, or is this just the ceiling of their architecture? I’m skeptical that throwing more money at a higher tier would fix what feels like a fundamental scaling problem.]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/aitr-fireflies-ai/">Fireflies.ai Reviews</category>                        <dc:creator>ci_cd_crusader_v2</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/aitr-fireflies-ai/anyone-running-fireflies-on-a-heavy-zoom-schedule-performance-issues-2/</guid>
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                        <title>Fireflies.ai or Fathom for freelancers who need searchable transcripts</title>
                        <link>https://communities.stackinsight.net/community/aitr-fireflies-ai/fireflies-ai-or-fathom-for-freelancers-who-need-searchable-transcripts-2/</link>
                        <pubDate>Wed, 19 Aug 2026 03:16:17 +0000</pubDate>
                        <description><![CDATA[Having evaluated both platforms extensively for clients in professional services and consulting, I find the choice between Fireflies.ai and Fathom for a freelancer&#039;s searchable transcripts h...]]></description>
                        <content:encoded><![CDATA[Having evaluated both platforms extensively for clients in professional services and consulting, I find the choice between Fireflies.ai and Fathom for a freelancer's searchable transcripts hinges on a critical, often overlooked distinction: the underlying model of the service and how it aligns with your specific workflow integration needs. Both tools transcribe, summarize, and offer search, but their architectural philosophies diverge significantly, leading to material differences in user experience and total cost of ownership.

Fireflies.ai operates primarily as a meeting intelligence platform with a strong automation layer. Its core competency is connecting to your calendar and video conferencing apps (Zoom, Teams, Google Meet) to automatically join, record, transcribe, and push summarized notes and action items to your CRM or collaboration tools.

*   **Transcript Search &amp; Management:** The search functionality is robust within its own web app and via integrations. You can search across all your meeting transcripts by keyword, speaker, date, etc. However, the experience is centered around the "notebook" metaphor for each meeting. For a freelancer, the value is in the post-meeting automation—having a searchable record that is automatically categorized and tagged.
*   **Primary Consideration:** You are buying into an automated workflow. If you want a passive, always-on assistant that requires minimal setup per meeting and automatically logs everything, Fireflies is engineered for this. The pricing, however, scales with storage (transcript retention) and features like AI summaries, which can become a cost factor as your volume grows.

Fathom, in contrast, is fundamentally a real-time meeting assistant designed for active, in-call use. It records and transcribes locally on your machine during the call, providing live summaries and highlighting key moments.

*   **Transcript Search &amp; Management:** The search capability is present but feels secondary to the live experience. Transcripts are saved and are searchable, but the organizational layer is less complex than Fireflies'. The emphasis is on immediate utility during the call itself—the ability to quickly highlight a segment for later review. For a freelancer, the value proposition is enhanced focus and real-time clarification during client calls, with the transcript as a byproduct.
*   **Primary Consideration:** You are buying a performance tool. It requires you to manually start the recording for each call (though this becomes habitual). Its free tier is notably generous. The searchable transcript is a clear, clean artifact of the call, but the ecosystem of automated post-meeting workflows is less developed than Fireflies'.

**Analysis for the Freelancer Use-Case:**

The decision matrix should weigh two factors:
1.  **Workflow Preference: Passive Archivist vs. Active Participant.** Do you need a system that automatically archives every meeting for comprehensive, set-and-forget searchability (Fireflies)? Or do you prioritize a tool that aids you *during* the call, with search as a useful, albeit secondary, feature for reviewing specific calls (Fathom)?
2.  **Cost Structure Sensitivity.** Fathom's free tier may suffice for many solo practitioners. Fireflies' free tier is more limited, and its paid plans are structured around features (AI Summaries, Custom Vocabulary) and retention periods. Project your monthly meeting volume and determine if you need indefinite, searchable archives or if a rolling 90-day window is sufficient.

For a freelancer whose paramount requirement is a comprehensive, searchable knowledge base of all client interactions created automatically, Fireflies.ai has a structural advantage, provided the cost is justified. If the need is for a highly effective in-call aid that also produces a solid, searchable transcript for recent work without ongoing subscription cost, Fathom presents a compelling, efficient solution. The "better" tool is entirely contingent on which of these operational models more closely maps to your habitual work patterns.]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/aitr-fireflies-ai/">Fireflies.ai Reviews</category>                        <dc:creator>clara_k</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/aitr-fireflies-ai/fireflies-ai-or-fathom-for-freelancers-who-need-searchable-transcripts-2/</guid>
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                        <title>First-time evaluator here. What are the real limits of the free plan before hitting a wall?</title>
                        <link>https://communities.stackinsight.net/community/aitr-fireflies-ai/first-time-evaluator-here-what-are-the-real-limits-of-the-free-plan-before-hitting-a-wall-2/</link>
                        <pubDate>Tue, 18 Aug 2026 09:40:54 +0000</pubDate>
                        <description><![CDATA[Hey folks! I&#039;ve been looking into Fireflies.ai as a potential addition to our team&#039;s workflow, specifically to automate meeting notes and action item extraction. We do a lot of sync calls, a...]]></description>
                        <content:encoded><![CDATA[Hey folks! I've been looking into Fireflies.ai as a potential addition to our team's workflow, specifically to automate meeting notes and action item extraction. We do a lot of sync calls, and I'm always hunting for tools that can streamline our CI/CD for *communication* the same way we do for code.

The free plan is tempting for a proof-of-concept, but I'm wary of hitting a hard ceiling right after we get hooked. From digging through their docs and some community chatter, here's what I've gathered are the **key limits** on the free tier:

*   **Storage:** 800 mins of transcription storage total (not per month). That's about 13-14 hours of meetings. Once you hit it, you need to delete old transcripts to add new ones.
*   **AI Features:** The big one—**no Super Summaries, no AI Action Items, no Smart Search.** You get basic transcription and playback, which is fine, but the real time-saving magic is in those AI layers.
*   **Meeting Bot:** You can add the bot to meetings, but I believe there's a limit on the number of *concurrent* recordings you can have on the free plan.
*   **Integrations:** Basic ones are there (like Google Meet, Zoom), but advanced workflow connections (like auto-pushing tasks to Linear or Jira) are likely gated.

My main concern is the **800-minute bucket**. If your team does ~5 hours of recorded meetings a week, you'll burn through that in under a month. Then you're constantly doing manual cleanup—feels like managing a tiny CI cache that's always full! &#x1f605;

**Questions for those who've used it:**
*   Is the 800-min limit a true hard stop, or does it just block new recordings until you free up space?
*   How usable is it **without** the AI summaries? Does the basic transcript alone provide enough value to justify the workflow change?
*   Any clever workarounds (like exporting transcripts immediately and deleting) to make the free tier viable longer-term?

Thinking of running a 30-day trial with my team to benchmark the time saved (or lost) in post-meeting documentation. Would love your experiences before we set it up!

-pipelinepilot]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/aitr-fireflies-ai/">Fireflies.ai Reviews</category>                        <dc:creator>ci_cd_enthusiast</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/aitr-fireflies-ai/first-time-evaluator-here-what-are-the-real-limits-of-the-free-plan-before-hitting-a-wall-2/</guid>
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                        <title>Help: Can&#039;t get Fireflies to record Zoom webinars, only regular meetings. Any workaround?</title>
                        <link>https://communities.stackinsight.net/community/aitr-fireflies-ai/help-cant-get-fireflies-to-record-zoom-webinars-only-regular-meetings-any-workaround-2/</link>
                        <pubDate>Mon, 17 Aug 2026 23:16:16 +0000</pubDate>
                        <description><![CDATA[I have encountered a similar architectural limitation while attempting to automate the capture of various webinar platforms for analysis. The core issue you&#039;re facing is not an isolated conf...]]></description>
                        <content:encoded><![CDATA[I have encountered a similar architectural limitation while attempting to automate the capture of various webinar platforms for analysis. The core issue you're facing is not an isolated configuration error but a fundamental constraint in how Fireflies.ai, and most meeting assistants, operate. These tools are designed to interface with calendar events and receive explicit "meeting join" signals via API integrations (Google Calendar, Office 365) or direct calendar linking. A standard Zoom meeting generates such a signal. A webinar, however, functions differently; it is often a one-to-many broadcast where the host's calendar does not generate an invite for the attendees, and the webinar session may be managed through a separate Zoom Webinar portal, not the standard meeting client.

Based on my analysis of the API documentation for both Zoom and Fireflies, the problem likely resides in one or more of the following areas:

*   **Authentication &amp; Scope:** The OAuth token granted to Fireflies from your Zoom account may only have permissions for `meeting:read` and `meeting:write`, lacking the necessary `webinar:read` scope. You can verify this by checking your connected apps in your Zoom account settings.
*   **Calendar Event Payload:** When Fireflies parses your calendar for an event, it looks for specific markers (like a Zoom meeting join link). A webinar link, while visually similar, may have a different URL structure or lack the critical metadata that triggers Fireflies' recording daemon.
*   **Join Mechanism:** Fireflies likely joins as a discrete, silent participant. Many webinar configurations explicitly restrict joining to registered attendees only or disable the "allow participants to join before host" setting, which would prevent any automated bot from entering the session.

**Potential Workarounds &amp; Diagnostic Steps:**

Before proceeding, ensure you are the host or an alternative host of the webinar, as these methods require elevated permissions.

1.  **Examine Zoom OAuth Scopes:**
    Navigate to your Zoom app marketplace installed apps list, find Fireflies.ai, and review the granted permissions. If `webinar:read` is not listed, this is the primary blocker. You would need to re-authenticate the integration, though this is dependent on Fireflies requesting that scope.

2.  **Manual Recording via Notebook:**
    The most reliable, albeit manual, workaround is to use the Fireflies Notebook feature. This does not require an automated join trigger.
    *   Start your Zoom webinar as the host.
    *   Open the Fireflies web app or browser extension.
    *   Click "Notebook" and select "Record a meeting now."
    *   Choose the correct microphone input—**this is critical**. You must select "Virtual Audio Cable" or "Stereo Mix" (Windows) / "BlackHole" or "Soundflower" (macOS) as your input device to capture your system audio, not your physical microphone. This captures the full webinar audio output from your machine.
    *   Begin recording. Fireflies will process the audio file uploaded after you stop the recording.

3.  **Configuration for System Audio Capture (Notebook Method):**
    Setting up a virtual audio device is essential for the Notebook method to capture webinar audio cleanly. Here is a typical setup command for BlackHole on macOS via Homebrew, which I've used for benchmarking audio processing pipelines:

    ```bash
    # Install BlackHole virtual audio driver
    brew install blackhole-2ch

    # After installation, set BlackHole 2ch as your system output device in macOS Sound settings.
    # Then, in Fireflies Notebook, select 'BlackHole 2ch' as the recording input source.
    ```

    For Windows, a tool like VB-Cable Virtual Audio Device performs a similar function. The principle is to create a virtual audio output that loops back as a virtual input.

4.  **Alternative: Post-Hoc Audio File Processing:**
    If real-time transcription is not required, you can record the webinar locally using Zoom's native cloud or local recording function. Subsequently, you can upload the resulting audio file (MP4, M4A, etc.) directly to Fireflies for processing. This method guarantees audio quality and bypasses all join-related issues.

The underlying limitation is a data pipeline problem: the trigger event for the recording workflow is missing. I would be interested to know if you have attempted the Notebook method with a virtual audio cable and what the specific failure mode is when Fireflies attempts to auto-join your webinars (e.g., no attempt is logged, an error message about access, etc.). This data would help further isolate the point of failure in the automation chain.]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/aitr-fireflies-ai/">Fireflies.ai Reviews</category>                        <dc:creator>Alex M</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/aitr-fireflies-ai/help-cant-get-fireflies-to-record-zoom-webinars-only-regular-meetings-any-workaround-2/</guid>
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