Granola vs Maith

Granola and Maith are both productivity tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

Granola

Granola sidesteps that friction entirely by running locally on your Mac, Windows, or iOS device, capturing audio through the system rather than injecting a bot into the call. After the meeting ends, you trigger note enhancement manually — Granola structures what was said into summaries, action items, and searchable records without anyone on the other side knowing a transcript is being built. The workflow is fast for solo professionals and executives grinding through back-to-back calls. The ceiling appears when your team needs real-time collaboration, live transcription during the call, or CRM sync that isn't stitched together manually. Teams that hit that ceiling tend to move toward Fireflies or Otter, which offer in-call bot presence in exchange for the privacy trade-off.

Maith

Maith organizes AI exploration of open problems — Riemann Hypothesis, P vs NP, Collatz, Goldbach, and roughly twenty others — into a structured workflow that keeps generated ideas, numerical evidence, and symbolic output in separate lanes, so you can't accidentally treat one as the other. Each conjecture lives in its own directory, which means your lemma dependencies, small-case experiments, and falsification attempts stay auditable rather than buried in a chat thread. The workspace is self-hosted and open-source with no license file published, so production use requires legal review before deployment in institutional settings. There is no API, no autonomous agent loop, and no GUI — this is a code-and-file workflow, not a drag-and-drop canvas.

Attribute	Granola	Maith
Pricing	Paid	Free
Price	$14/mo	—
Free trial	No	No
Open source	No	Yes
Has API	Yes	No
Self-hosted option	No	Yes
Platforms	Mac, Windows, iPhone	GitHub, Python
Released	2024-05	—
Pros	No bot joins the call, so confidential client conversations, investor meetings, and sensitive executive discussions proceed without a visible recording indicator changing the dynamic in the room. Post-call AI note enhancement structures raw audio into summaries and action items automatically, which means professionals running five or six meetings a day are not spending evenings reconstructing what was decided. Local audio capture at the system level rather than a third-party stream, so the privacy exposure that comes with a bot-based recorder is avoided by design rather than by policy. Shared folders and AI-powered search across meeting records, so a product or sales leader can surface decisions and context from past calls without asking someone to resend notes or dig through Slack. API and MCP access for teams that want to route structured meeting output into other tools — meaning Granola can act as a data source for downstream workflows rather than a dead-end repository.	Separates AI-generated ideas from numerical evidence and symbolic output into distinct artifacts, so a plausible narrative never gets mistaken for a proof step during review. Pre-structured directories for roughly twenty named open problems ship with the repo, so you start with a scaffold rather than designing your own organizational scheme from scratch. Self-hosted and file-based, which means your conjecture work, lemma notes, and experiment outputs stay on your infrastructure — no data leaves to a third-party service. Adversarial falsification is built into the workflow design, so small-case counterexample searches and reproducible CAS experiments are first-class activities rather than afterthoughts. No proprietary lock-in to a specific AI provider — you wire in your own model or tool, so the workspace survives provider changes without restructuring your research artifacts.
Cons	There is no live transcription during the call. If your use case requires seeing what is being said in real time — for accessibility, live note-taking by a second participant, or in-call coaching prompts — Granola's post-hoc model does not solve that problem, and teams with those requirements move to Fireflies or Otter instead. CRM logging is not automatic. Sales teams that need customer conversation records to appear in Salesforce or HubSpot without a manual step are maintaining a copy-paste process or building their own API integration, at which point the time savings from automated note-taking shrink significantly. No self-hosted option exists. Organizations under data residency or regulatory constraints that prohibit cloud processing of meeting audio cannot deploy Granola without validating the vendor's data handling architecture first — and some will not clear that bar regardless of the answer. The tool is Mac, Windows, and iOS only. Teams with Linux users or Android-primary workflows hit a hard wall: those participants cannot run the local client, which breaks the privacy model for any call where the Linux or Android user is the one who needs the notes.	There is no formal proof verification integration: when your workflow requires machine-checked proofs rather than structured human review, Maith offers no path to Lean, Coq, or Isabelle, and teams doing formal verification abandon it for those environments immediately. No license file exists in the repository, so institutional or commercial use requires legal clarification before deployment — teams under compliance constraints cannot use it without resolving that gap first. The workflow is entirely file-and-code-based with no GUI, which means onboarding any collaborator who is not comfortable in a code environment requires building your own interface layer on top. Coverage is limited to roughly twenty pre-structured open problems — researchers working outside that set get no scaffold and must design their own directory conventions, at which point the reproducibility guarantees depend entirely on their own discipline rather than the tool's structure.

Bottom line

Granola is paid while Maith is free; Maith is open source; only Granola exposes a public API. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between Granola and Maith?

Granola is Paid, while Maith is Free and open source. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is Granola better than Maith?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.

Granola vs Maith: which should I pick?

Pick Granola if its pricing model, openness, or platform fit matches your constraints; pick Maith otherwise. Check free-trial availability on each listing if you want to test before committing.

Comparison data is sourced and verified by the AIDiveForge data pipeline. AIDiveForge is editorially independent.