Alright, let's cut through the marketing fluff. You're asking about the "best" meeting note taker for a small engineering team, but what you're *really* asking is: "What's the most cost-effective tool that won't leak our architecture discussions to the void while actually saving us engineering hours?" I've been down this rabbit hole, and let me tell you, the pricing models for these AI scribes can have more hidden line items than a poorly tagged AWS bill.
For your stack (Slack + Google Meet), you've got a few contenders, but the operational overhead and "gotchas" vary wildly. Let's break it down like a FinOps report.
**The Usual Suspects & Their Billing Anomalies:**
* **Fireflies.ai:** Good integration depth. The "Unlimited" plan is a trap for teams that actually meet a lot. It's unlimited *storage*, not unlimited transcription minutes. You'll hit the minute cap fast and then it's pay-per-minute overages. Feels like getting charged for data transfer out after you thought you had a flat rate.
* **Otter.ai:** The veteran. Solid quality. Their business plan forces you into seats, and if your 5 engineers have 15 stakeholders popping into meetings occasionally, you're suddenly buying 20 seats. Classic bundled resource problem—like paying for a z1d instance when you just need a t3.micro for burst traffic.
* **Sembly AI:** This is the one I've been stress-testing. It's the "serverless" option in this space. You pay for credits (minutes), which is beautifully granular. No per-seat nonsense. The Slack integration is slick—it drops summaries directly into the channel. The **major pitfall**? It defaults to transcribing *every* channel meeting. You'll burn credits on that 2-minute "hey, you there?" huddle. You need to configure it like you'd configure a CloudWatch budget alarm.
**My Sembly Configuration for Cost Control:**
You absolutely must set this up from day one. Here's a snippet of the logic you should enforce, ideally through their onboarding or via a Slack workflow.
```yaml
# Sembly Cost-Saving Policy (Pseudocode)
IF meeting_duration < 5 minutes:
DO_NOT_TRANSCRIBE
IF meeting_participants < 2:
DO_NOT_TRANSCRIBE
IF meeting_title CONTAINS ("social", "coffee", "chit-chat"):
DO_NOT_TRANSCRIBE
# Explicitly invite Sembly only to channels:
# #project-argon, #infra-review, #postmortem
# Never add it to #general or #random.
```
The quality for technical meetings is... acceptable. It stumbles on deep acronyms (heard it call "AWS S3" "AWS Success" once) and complex architecture diagrams are lost. But the action item and decision extraction is where it saves time. It's like having a naive reserved instance recommendation—not perfect, but a starting point.
**The Verdict:**
For a 5-engineer team, **Sembly on the "Professional" pay-as-you-go credits** is the most financially sane. It's operational expenditure (OpEx) that scales linearly with use. Treat it like a utility. The others try to lock you into a capacity reservation you don't need.
Just remember to tag your meetings. Or better yet, set up a Lambda that pings you when your credit burn rate exceeds $X per day. Because unchecked, these tools will quietly consume budget like an unattended EC2 instance left running over the weekend.
Your cloud bill is too high, and your meeting note-taker bill will be too, if you're not careful.
Hey, this post hits close to home. I'm a junior PM at a series A startup (20 people, 7 engineers), and I just went through this exact vendor bake-off last quarter. We run on Slack and Google Meet and we've been using the tool I picked in production for about three months now.
My evaluation was mostly based on the pricing traps you mentioned and some engineering-specific needs. Here's how I broke it down.
1. **True Cost for Occasional Guests:** Most tools charge per seat. With engineers, product, and occasional guests from sales or legal, a 5-engineer team can easily have 10+ "occasional" attendees per month. I looked for per-host pricing. For example, **Otter Business** is ~$20/user/month, so 5 seats is $100/month minimum, and guests count. **Fireflies** "Unlimited" is ~$19/user/month with a 6,000 minute cap per user *per year*, which we'd blow through in a quarter. The winner for us was **Grain**, which charges ~$15/month *per host* (the meeting creator) and lets unlimited guests join without a paid seat.
2. **Handling Engineering Jargon & Code:** I tested each by recording a segment of our sprint planning where we discussed API endpoint structures. **Otter** consistently capitalized random words like "Post" or "Get." **Fireflies** did better with common terms but mangled specific variable names. **Grain** and **Fathom** (another option) both had a "vocabulary boost" feature where you could upload a glossary of terms. Fathom's was manual upload only, while Grain's learned from past transcripts automatically after a few meetings, which was a small but real time save.
3. **Slack Integration Depth:** You need more than just a "post to channel" button. The key was whether the tool could post summaries to a private channel automatically *and* thread follow-up discussion. **Fireflies** does this well with its Fred bot, creating a dedicated thread for each meeting. **Grain** creates a dedicated Slack channel per recorded meeting, which some found cluttered. **Fathom** only posts a link to the summary in the channel you specify, no auto-threading.
4. **Action Item Tracking & Noise:** A big sell is turning discussion into tickets. In practice, the AI-generated "action items" were often useless ("John will look into the bug"). **Fireflies** had the most detailed AI task creation but it generated 2-3 false positives per meeting. **Grain** was more conservative, only flagging sentences with clear commitment language, but that meant it missed subtler assignments. We ended up disabling auto-task creation on all of them; the real value was just having a searchable transcript.
I went with **Grain** for our team. The per-host pricing model was the deciding factor because of our high number of guest stakeholders, and the automated glossary learning smoothed out the engineer-specific terminology after a few weeks. If your team never has guests and you need the deepest Slack integration with perfect threading, Fireflies is probably the better call, but watch that annual minute cap like a hawk. To make it really clean, tell us your average number of meetings per week and how often non-engineers (like product managers or designers) are in those calls.
Spot on about the per-seat pricing being a mismatch for real-world meeting attendance. You mentioned "data transfer out" on AWS bills, and that's the perfect analogy. The real gotcha with the minute caps, like Fireflies has, is that they often count *all* audio processed, not just unique meeting minutes. If you have it auto-join a recurring sync and record, and three people have poor connections causing the tool to re-buffer streams, you can burn through your monthly pool on phantom minutes.
We ran a test last quarter: one 60-minute meeting with four participants, across three different services. The reported "minutes used" varied from 60 to nearly 240. You have to dig into their docs to find the multiplier they apply for concurrent speakers or connection issues. It turns your cost model into a variable you can't control.
Benchmarks or bust