Maith vs Makeform

Maith and Makeform 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.

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.

Makeform

Makeform is a freemium form builder covering the standard territory: lead capture, surveys, event registrations, job applications, and product feedback. The free tier is genuinely open-handed — no submission limits reported, which means small teams and early-stage products can run real volume without a credit card. Where the ceiling appears is in advanced features and integrations: heavier automation, priority support, and richer data tooling are paid-only features. Teams running enterprise workflows or complex conditional logic will hit that wall and either upgrade or move to a more configurable alternative. For straightforward form-to-spreadsheet pipelines, the free tier holds.

Attribute	Maith	Makeform
Pricing	Free	Paid
Price	—	$24/mo
Free trial	No	No
Open source	Yes	No
Has API	No	Yes
Self-hosted option	Yes	No
Platforms	GitHub, Python	Web-based SaaS platform; supports desktop and mobile browsers
Released	—	2025
Pros	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.	Unlimited forms and submissions on the free tier, so a startup validating a product or running a lead campaign doesn't hit a submission wall mid-launch. Chat-prompt form creation, which means a non-technical marketer or HR manager can generate a working form without touching a drag-and-drop canvas or reading configuration docs. API access included, so engineering teams can pipe response data directly into a CRM or data warehouse without manual CSV exports. MCP server compatibility, so teams building tool-connected workflows can include Makeform as a data-collection node without building a custom integration from scratch. Broad use-case coverage — lead gen, surveys, event registration, job applications, and user research — which means one tool handles the form layer across multiple teams rather than each team procuring separately.
Cons	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.	Advanced automation, richer analytics, and priority support are paid-only features — a team running a high-volume lead operation that needs real-time CRM sync or response scoring hits that wall quickly and either pays up or migrates to a tool like Typeform or Jotform where those features are more central to the product. No self-hosted option, which means teams in regulated industries or with strict data-residency requirements cannot keep response data on their own infrastructure — a hard stop that sends those teams to open-source alternatives regardless of how the free tier is priced. Complex conditional logic — forms that branch based on previous answers across multiple paths — is not a documented strength of chat-generated form builders; teams managing multi-path screening flows (job applications with qualification gates, for example) find themselves manually editing or abandoning generated output.

Bottom line

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

Frequently asked questions

What is the difference between Maith and Makeform?

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

Is Maith better than Makeform?

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.