Need honest feedback on Fireflies AI before I commit

Ai Tools
1

I’ve been testing Fireflies AI for meetings and note‑taking, but I’m not sure if it’s worth fully adopting for my team. Some transcripts seem inaccurate and I’m worried about privacy, pricing, and how it compares to other AI meeting assistants. Can anyone share real‑world experiences, pros, cons, and whether it’s reliable enough for daily business use?

2

I’ve run Fireflies for a small team over ~6 months. Here is the blunt take.

Accuracy

  • For clear audio on Zoom/Meet, we saw about 90–93 percent word accuracy.
  • For accents, crosstalk, or bad mics, it drops fast.
  • Action items and summaries are decent, but you still need a human skim.
  • If you expect “no manual notes ever again”, you will be disapointed.

Privacy

  • It records and stores audio + transcripts on their servers.
  • You need to check:
    • Where data is stored (region).
    • Retention settings.
    • Who in your workspace can see which calls.
  • For clients with NDAs or sensitive topics, we disable it or redact after.
  • Make sure your meeting invites and onboarding tell people it is recording. Some people freak out later if they were not told.

Pricing

  • The free plan is fine to test, not great for full team use.
  • Pro is affordable for small teams, but once you go org-wide it adds up fast.
  • Compare cost per active user, not per seat you think you will use. Idle seats waste money.
  • For many teams, having only “power users” on paid plans works better than full rollout.

Comparison to others

  • Otter:
    • Better live transcription in my experience.
    • UI feels more focused on notes.
    • Pricing similar tier wise.
  • tl;dv / Fathom / Tactiq:
    • Tighter focus on meeting notes, less “AI assistant” fluff.
    • Some have stronger privacy docs and better controls.
  • If you live in Google Meet or Zoom, test each tool for 3 real meetings and compare:
    • Accuracy
    • How long it takes you to find a quote later
    • How teammates react to the bot joining

Workflow fit

  • Fireflies works best if:
    • You record most external calls.
    • You share timestamped notes across teams.
    • You search a lot across past meetings.
  • It performs worse if:
    • You already keep good written notes.
    • Your calls involve sensitive info.
    • Your team hates bots popping into meetings.

Practical steps before you commit

  1. Run a 2 week test with 3–5 people, not the whole company.
  2. Compare the transcript with a human summary on 5 calls, see where it fails.
  3. Get legal or security to read the DPA, ToS, retention policy.
  4. Decide rules. For example:
    • No Fireflies on legal, HR, or confidential client calls.
    • Delete raw audio after X days.
  5. Price it out vs Otter and one other competitor for the same number of active users.

My bottom line.

  • Worth it if your team spends a lot of time in meetings and you accept “AI notes plus quick human edit”.
  • Not worth it if you need high accuracy, strong privacy guarantees, or detailed notes for compliance.
3

We’ve used Fireflies across sales + product + CS for a year. Net: it’s “useful background automation,” not “single source of truth,” and that distinction matters a lot.

On @sterrenkijker’s points:

1. Accuracy & expectations

I’d actually put it a bit lower than 90–93% for real-world teams. If you have:

  • multiple people
  • people talking over each other
  • half the team on cheap laptop mics

…it can feel more like “80% and sometimes annoying.” For 1:1s or clean audio, it’s solid. For busy project calls, we treat it as:

  • Searchable memory of “roughly what was said”
  • Way to grab quotes and timestamps

If you’re hoping to stop taking any manual notes, that’s where people get mad at it. What worked for us:

  • One person still owns 3–5 bullet “human summary” in the doc
  • Fireflies is backup: timestamps, exact phrasing, who said what

When people rely only on the AI summary, context and nuance get lost and bad decisions happen.

2. Privacy & trust

I’m a bit more skeptical than sterrenkijker here.

The core issues:

  • It sits in the middle of a lot of your conversations
  • Non‑technical stakeholders don’t really understand what that means
  • Once it’s culturally “normal,” people forget to question it

What we had to do that I’d strongly suggest:

  • Make an internal policy doc: “When Fireflies is allowed / not allowed”
  • Explicit consent rule: if anyone on the call says “no,” we kill the bot
  • Quarterly review of what’s actually stored and shared

Also: if you’re in a regulated space (health, finance, gov), I would not treat Fireflies as compliant documentation. It’s a convenience tool, not a system of record.

3. Pricing & rollout strategy

Where I disagree slightly: I don’t love the “only power users get it” approach long term. That created have/have‑not dynamics for us:

  • Some teams had crystal‑clear searchable history
  • Others had nothing and felt left out

We ended up with:

  • Fireflies on only for specific meeting types, but
  • Everyone in those teams has access to the workspace

So instead of “few power users,” we did:

  • Narrower use cases
  • Broader access

It was easier politically and more consistent culturally. Cost-wise, this meant negotiating and being ruthless about:

  • Removing inactive users every quarter
  • Turning off recording for low-value recurring meetings

4. Comparison with others (and how to test fairly)

My take:

  • Otter: better raw live transcription, worse org‑wide meeting capture workflow for us
  • Fathom / tl;dv: nicer UX, but less flexible if you want more “repository” vibes

Big thing: don’t compare tools in different situations. We only got clarity when we:

  • Took the same recurring meetings
  • Ran Fireflies vs competitor on alternating weeks
  • Measured: how often do we actually go back and use the notes?

Surprise outcome: the usage numbers mattered more than pure accuracy. A 92% accurate transcript nobody ever opens is worth less than an 85% one people actually search and clip.

5. How to decide if you should commit

If you’re on the fence, ask these:

  • Do we really revisit past calls, or do we just think we will?
  • Do we have legal / compliance constraints that make third‑party audio storage scary?
  • Are we okay telling every client “We record with an AI notes tool, is that okay?” every time?

My personal rule of thumb for Fireflies:

  • Good fit if:

    • You have lots of external calls
    • You often say “Who remembers what we decided on that call?”
    • Your team is okay with a bot quietly joining

  • Bad fit if:

    • Your work is highly sensitive or regulated
    • You already have strong note takers and written rituals
    • Your team hates any feeling of being monitored

If you already feel uneasy about privacy and the transcripts you’ve seen feel hit‑or‑miss, I’d treat this as “pilot tool,” not “core infrastructure.” Keep it optional, tightly scoped, and review in a couple months instead of locking the whole team into it.

4

Short version: treat Fireflies AI as “ambient capture,” not a replacement for human intent. If that mental model feels acceptable, it can be worth keeping; if you want zero‑maintenance, perfectly accurate notes and airtight privacy, you will stay annoyed.

Here’s a more structured, no‑nonsense breakdown.

Where I disagree a bit with @sterrenkijker

They’re right about expectations and policy, but I think they understate two things:

  1. Value of partial accuracy for internal calls
    Even “80% and sometimes annoying” can be huge for:

    • Engineering / product standups
    • Retro / discovery sessions
    • Internal alignment calls

    People rarely need verbatim text. They need:

    • “When did we mention this?”
    • “What did we promise roughly?”

    Fireflies AI is surprisingly good here, as long as you are fine with scanning around timestamps.

  2. Over-focusing on accuracy misses workflow value
    I’d worry less about the sentence‑level mistakes and more about:

    • How quickly people can jump to key moments
    • How easy it is to share a snippet with context
    • Whether folks actually use the workspace during follow‑ups

    Some tools with slightly better transcription feel slower and clunkier in real use. Fireflies AI is not the slickest UX on earth, but it is decent at giving you a central “meeting memory” without too much friction.

How I’d actually decide whether to commit

Instead of just testing transcripts, test behaviors:

  1. Run a 4‑week behavior pilot

    • Pick 3 recurring meeting types that matter:
      • Sales / customer calls
      • Product discovery / design reviews
      • Internal project syncs
    • For each meeting:
      • Require that 1 follow‑up action uses Fireflies AI
        Examples:
        • Paste an auto‑generated summary into your project tool, edit it, and see how much you have to fix
        • Grab 2 snippets & share them with someone who missed the call
        • Use search to answer “what did we say last week about X?”

    You are not measuring “how pretty is the transcript,” but:

    • How often did Fireflies AI save someone from re‑asking a question
    • How often did it speed up writing follow‑ups
    • How often did people open it without being reminded

  2. Ask your team 3 questions after the pilot

    • “If this disappeared tomorrow, what would hurt?”
    • “What did you stop doing because Fireflies AI existed?”
    • “What meetings should it never join?”

    If the answers are vague or lukewarm, do not roll it out broadly.

Privacy & risk, without the hand‑waving

Instead of just worrying in the abstract, categorize your meetings:

  • Red zone (no Fireflies AI):

    • Legal strategy
    • HR issues, performance, layoffs
    • Anything involving protected health / financial data
    • Board‑level or investor‑sensitive topics

  • Amber zone (case by case):

    • Client calls that might include confidential numbers or roadmaps
    • Partnership negotiations
    • Internal meetings with heavy personal or political angles

  • Green zone (default Fireflies AI):

    • Demos
    • Regular project syncs
    • Non‑sensitive internal workshops and brainstorming

Make this a written rule, not a vibe. If you cannot confidently list “red zone” meeting types, you probably should not normalize an AI recorder across all calls.

Also, one concrete check:
Ask yourself, “If a particular client demanded an export of all calls involving them, would we be comfortable handling that?” If the honest answer is no, limit Fireflies AI to low‑risk meetings only.

Fireflies AI vs others (not just accuracy)

You mentioned comparing tools. I’d look at these specific dimensions:

  1. Control of recording

    • How easy is it to stop the bot mid‑call without breaking flow?
    • Can non‑admins stop it? This matters a lot for trust.

  2. Granularity of sharing

    • Can you easily keep sensitive calls in a restricted folder?
    • Is there a clear “private vs team‑wide” toggle people actually understand?

  3. Friction to re‑use content

    • Is it quick to get a short snippet into email / Slack / your CRM?
    • Can sales easily attach snippets to deals?
      Sometimes a tool with weaker AI but great workflows beats a smarter one.

Compared with alternatives like Otter or Fathom, Fireflies AI tends to sit in a middle ground: decent capture, OK summarization, solid enough hub features. @sterrenkijker is right that some competitors are nicer on UX or raw transcription, but that does not always translate into more usage.

Pros & cons of Fireflies AI in practical terms

Pros:

  • Centralized meeting memory across teams
  • Easy to retroactively clarify “what did we agree on?” for non‑sensitive topics
  • Reduces reliance on one person being the scribe every time
  • Decent search and timestamping for “find that moment when X said Y”
  • Works reasonably well as a cross‑department repository

Cons:

  • Not trustworthy as a single source of truth for critical decisions
  • Accuracy drops fast with crosstalk, accents, or bad mics
  • Can normalize passive recording culture if you are not strict about boundaries
  • Extra cognitive overhead explaining “what is this bot?” to external guests
  • Risk of people over‑trusting AI summaries and skipping human follow‑ups

My recommendation for your situation

Given that you already feel uneasy about accuracy and privacy:

  • Keep Fireflies AI in pilot / optional status.
  • Limit it to green‑zone meetings where:
    • There is clear value in searchable history
    • No regulated or sensitive info is discussed
  • Require that each meeting still has a human‑owned 3–6 bullet summary in your existing system (docs, project tool, CRM).
  • Re‑evaluate after 6–8 weeks based on:
    • How often it was actually used to answer a question or support a decision
    • Whether any privacy complaints or awkward moments came up

If those 6–8 weeks do not produce at least a handful of “this really saved us” stories, treat Fireflies AI as a nice‑to‑have for a few power users, not as a team‑wide standard.