AI Transcription Tools Compared: Whisper, Otter, Fireflies

Transcription is one of the few areas where AI quietly went from novelty to boring utility. It works. The interesting question is no longer whether a machine can write down what was said, but which of the three available approaches suits how your business actually runs.

Those approaches are: run the model yourself, use a note-taking app built around meetings, or use a sales-oriented tool that joins the call and reports on it afterwards. Whisper, Otter, and Fireflies are the recognisable names in each camp.

Accuracy is not one number

Vendors publish accuracy figures. Treat them as marketing, because accuracy depends almost entirely on conditions the vendor does not control.

What genuinely moves accuracy for a local business:

• Microphone quality, which matters more than the model. A headset beats a laptop microphone across the room every time.
• Crosstalk. Two people talking simultaneously degrades every system.
• Accents and multilingual speakers, where performance varies noticeably between tools.
• Jargon and proper nouns. Street names, product codes, and surnames are where errors cluster, and they are the words you most need correct.
• Speaker separation, which is a different problem from transcription and often the weaker feature.

Test with your own recording rather than trusting a benchmark. Ten minutes of a real meeting tells you more than any comparison table.

The three approaches

Whisper: the model itself

OpenAI's Whisper is open and can run on your own machine or through a paid interface. Two properties make it interesting for a small business. It handles a wide range of languages and accents well, and when run locally the audio never leaves your computer, which resolves most privacy questions outright.

The cost is convenience. Local Whisper is a file-in, text-out tool. No meeting bot, no summary, no search across past calls, and setup requires more comfort with software than most owners want. Suited to recorded audio you already possess: voicemails, site walkthroughs, dictated notes, interviews you cannot upload anywhere.

Otter: the meeting notebook

Otter joins your calls, transcribes live, produces summaries, and keeps everything searchable in one place. The live transcript is genuinely useful for people who struggle to listen and write at once, and the interface is approachable enough that non-technical staff adopt it without training.

It is a general tool. It knows a meeting happened and what was said, but it does not know your sales process. Best for teams whose main need is recall.

Fireflies: the sales-oriented option

Fireflies also joins calls and transcribes, but the emphasis is on what happens afterwards: action items extracted, topics tracked across many calls, and a push into your CRM so the record updates without anyone typing. If you run a pipeline and forget to log calls, that integration is the feature you are buying.

The overhead is real though. It is more configuration than a solo operator needs, and the analytics only pay off with enough call volume to produce a pattern.

What actually differs in daily use

Raw transcript quality between the hosted services is close enough that it rarely decides anything. The differences that show up after a month are elsewhere.

Summary quality varies more than transcription quality, and summaries are what people actually read. Search across historical calls is the feature owners underestimate before they have it and rely on afterwards. Integration determines whether the transcript reaches the place you need it or sits in a separate app you stop opening. And meeting bots appearing as a visible participant changes the tone of client calls, which some businesses accept and others dislike.

Consent and privacy, which people skip

Recording law varies by state, and Connecticut's rules are not the most permissive. The safe practice everywhere is straightforward: announce recording before it starts, let anyone decline, and stop if they do. This removes the legal question entirely and costs you one sentence.

Beyond the law, consider what you are storing. A year of client calls is a detailed archive of other people's business, held under your account. Decide on a retention period and enforce it. If the material is sensitive enough that you would not want it on a vendor's servers, that is the argument for running Whisper locally rather than for hoping nobody asks.

Picking by use case

• Occasional recorded audio, privacy-sensitive: Whisper locally
• Team meetings, you want to remember what was agreed: Otter
• Client-facing sales calls feeding a pipeline: Fireflies
• Everything happens in one video platform already: check its built-in transcription first, since it may be adequate and free

That last point is worth pausing on. Zoom, Teams, and Google Meet all include transcription now. Before adding a subscription, check whether what you already pay for does the job. It frequently does.

Common questions

Good enough that editing is quick, not good enough to publish unread. Errors concentrate in proper nouns, technical terms, and passages where people talk over each other, which are often the parts that matter. Audio quality affects the result more than the choice of tool, so improve the microphone before switching services.

Assume yes. Recording rules differ by state and Connecticut's are stricter than the most permissive, so relying on one participant's consent is unwise. Announce it before the recording begins and allow people to decline. It takes a sentence, removes the ambiguity, and is simply better practice with clients.

The model is open and free to run on your own hardware, though you pay in setup effort and processing time. Hosted access through an API is billed by usage. The main reason a business chooses local Whisper is not cost but privacy, since audio processed on your own machine never reaches a third party.

It replaces the transcription, not the thinking. The transcript records what was said; deciding what mattered and what you committed to remains yours. Most people who use these well still write three or four lines of their own immediately after the call, then use the transcript to check details later.