Granola, Otter, Fireflies, and SpeechToDo Are Solving Different Problems

By SpeechToDo · May 17, 2026

Most comparisons between AI note tools start in the wrong place.

They ask which product has the best summary, the cleanest transcript, the most integrations, or the strongest meeting bot. Those are useful questions, but they hide the more important one:

What kind of work are you trying to preserve?

Granola, Otter, Fireflies, and SpeechToDo all sit near the same broad category from the outside. They all touch voice, transcription, notes, summaries, and follow-up work. But they are not solving the same problem.

Granola is built around better meeting notes for people who are actively in meetings. Otter is expanding from meeting transcription into a broader conversation knowledge system. Fireflies is built as a meeting intelligence workspace with many integrations and AI skills. SpeechToDo is being built around file-native voice artifacts that start in a user-owned workspace and become reviewable markdown.

Those are different bets.

The right choice depends less on a feature checklist and more on where you want the source of truth to live.

Start with the workflow, not the category

“AI notetaker” is now too broad to be a useful buying category.

A sales team, a solo founder, a product researcher, and a privacy-sensitive operator may all say they need better voice notes. In practice, they are asking for different systems.

One person wants a bot or assistant to join meetings and send summaries to the team. Another wants to write a few live notes during calls and have AI improve them. Another wants cross-meeting search across months of customer conversations. Another wants to drop audio files into a folder and get markdown artifacts they can inspect, edit, and move into their own system.

Those workflows overlap, but they should not be collapsed into one product decision.

The most useful question is:

Where should the durable artifact live after the AI has done its work?

If the answer is “inside a meeting assistant workspace,” tools like Granola, Otter, and Fireflies may be the right place to start. If the answer is “as files I own, beside the source recording, in a workflow I can inspect,” SpeechToDo is aiming at a different problem.

Granola: better notes for active meeting work

Granola describes itself as an AI notepad for people in back-to-back meetings. Its workflow is centered on turning a user’s own meeting notes plus a transcript into stronger notes after the meeting.

That is a sharp product idea.

The user is not just receiving a generic transcript. They can guide the output with their own notes, meeting context, and templates. Granola’s docs explain that enhanced notes are generated from the captured transcription, any raw notes the user took, and information from the calendar event. Its positioning is especially strong for people who are already taking meeting notes and want AI to fill in the gaps.

Granola also has an important product distinction: it does not use a meeting bot in the call. Its transcription docs say Granola runs on the user’s computer, uses system audio and microphone input, and is designed for live meeting transcription rather than importing pre-recorded audio files.

That makes Granola a good fit when the job is:

It is less directly aimed at a workflow where the user records arbitrary voice dumps, stores source audio in a local folder, and wants portable markdown outputs beside that source.

That does not make Granola worse. It means the center of gravity is different.

Otter: from meeting transcription to conversational knowledge

Otter has long been associated with meeting transcription. Its product now aims at a broader system of record for conversations.

Otter’s quick start materials describe a meeting assistant that can join meetings, capture slides, send summaries, record and transcribe conversations in real time, import audio or video files, share conversations, organize them in folders, and support collaboration through channels.

In April 2026, Otter also announced a larger “Conversational Knowledge Engine” direction: connecting conversations across teams and time, using accumulated meeting history as structured knowledge for future workflows.

That is an enterprise-shaped bet.

Otter is useful when the question is not only “what happened in this meeting?” but also “what has been said across many conversations, by many people, over time?”

That can matter for sales, recruiting, customer success, product research, and large teams where conversation history becomes organizational memory.

The tradeoff is that the workspace becomes central. If the user’s main goal is to build a long-lived conversation knowledge base inside a vendor system, that can be valuable. If the user’s main goal is to keep the durable artifact as a normal file that can live outside the app, then the center of gravity may be too different.

SpeechToDo is not trying to be the enterprise conversation graph. It is trying to make captured voice useful as owned files.

Fireflies: meeting intelligence and integrated follow-up

Fireflies is also solving a meeting-centered problem, but its angle is different again.

Fireflies describes itself as an AI notetaker assistant that helps users capture, transcribe, summarize, and search meetings in one workspace. Its current product surface includes a mobile app for in-person conversations, a desktop app for calls, dialer and API support, meeting search, integrations, and many AI skills for extracting follow-ups, scoring candidates, generating emails, and pulling structured details from conversations.

That makes Fireflies strong when the user wants meetings to flow into a broader business process.

For example, a sales or recruiting team may care less about a local markdown artifact and more about:

That is a legitimate product direction. Many teams want the meeting workspace and the integrations more than they want file ownership.

SpeechToDo starts from a narrower premise: the captured voice artifact should remain useful even without a heavyweight meeting intelligence workspace around it.

SpeechToDo: file-native voice artifacts

SpeechToDo is not trying to out-meeting the meeting assistants.

The initial product thesis is simpler:

Voice should become portable artifacts the user can own.

That means the durable outputs should be normal files whenever possible: transcripts, summaries, decisions, open questions, and candidate tasks. The user should be able to inspect those files, edit them, search them, archive them, delete them, or move them into another system.

The workflow is especially relevant for founders and operators who do not only record formal meetings.

They record:

Some of that audio may belong in a meeting assistant. A lot of it does not.

SpeechToDo is being built for the work that starts as captured thinking and needs to become a reviewable artifact. The point is not that a markdown file is more impressive than a dashboard. The point is that a markdown file is portable, inspectable, and easy to route into whatever system the user already trusts.

That is why the product keeps returning to the same boundary:

AI can help process the voice, but the file should remain the durable surface.

A practical chooser

A fair comparison should make the choice easier, not pretend one product is best for every user.

Choose Granola if your main workflow is live meeting note-taking and you want AI to improve notes you are actively shaping during the meeting.

Choose Otter if you want a mature conversation workspace that can capture, transcribe, organize, share, and increasingly connect meeting knowledge across a team or organization.

Choose Fireflies if meetings need to feed collaboration, sales, recruiting, support, or other integrated business workflows with summaries, search, and automation.

Choose SpeechToDo if your priority is turning voice capture into files you own: markdown transcripts, summaries, decisions, open questions, and candidate tasks that can live outside a proprietary dashboard.

That last workflow is narrower, but it is not small.

For a founder, the problem is often not “I need another meeting bot.” The problem is “I keep capturing useful thinking by voice, and I need it to become something I can reuse.”

The source of truth question

The real difference is the source of truth.

In a meeting assistant workflow, the product workspace often becomes the place where the transcript, summary, action items, and search experience live.

In a file-native workflow, the product helps create artifacts that can leave the product.

That distinction affects everything:

There is no universal right answer. Teams that need shared meeting intelligence may benefit from a workspace-centered model. Individuals who want durable, inspectable artifacts may prefer a file-centered model.

The important thing is to choose intentionally.

Different problems deserve different tools

Granola, Otter, and Fireflies are useful products because meetings are still one of the main places work happens.

SpeechToDo is being built from a different observation:

Not every important voice note is a meeting, and not every useful output should live inside a meeting workspace.

Some captured thinking should become a file. Some tasks should remain candidate tasks until reviewed. Some summaries should sit beside the source audio. Some decisions should be copied into the user’s existing system instead of trapped in another dashboard.

That is the workflow SpeechToDo is built for.

If you want meeting intelligence, start with a meeting intelligence tool. If you want file-native voice artifacts, start with the voice notes to markdown workflow that keeps the artifact portable.

For more specific comparisons, see the Granola alternative, Otter alternative, and Fireflies alternative pages. If the file-native workflow is the one you want to try, the paid beta is open from the SpeechToDo home page.

Sources checked