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ml 12

The ML category is a broad collection of 674 tools that apply machine learning across industries and functions, from healthcare documentation and legal research to user research, code generation, and content creation. It captures AI applications that do not fit cleanly into a single vertical.

Voicemod

general

Real-time voice changer for gaming and streaming

Paid 53 · 43,482 votes

Dialpad

general

AI contact center for omnichannel communication

Paid 52 · 29,208 votes

Respeecher

general

Professional AI voice generation for production

Paid 42 · 38,821 votes

Research Studio

general

AI-enhanced analysis for user research data

Paid 37 · 53,318 votes

Metaforms

general

Process survey data and generate insights with AI

Paid 37 · 47,628 votes

Maibrain

general

Business intelligence from multiple data sources

Paid 37 · 45,196 votes

Imgproof

general

Text checking in images and ads

Paid 36 · 29,783 votes

Nativish

general

AI writing tool that helps you write confidently in a second language

Paid 36 · 25,516 votes

Split Prompt

general

Break down complex prompts for better LLM responses

Paid 36 · 23,727 votes

Mixpeek

general

Search text, images, and video together

Paid 36 · 22,392 votes

Listen411

general

Transcribe podcasts in 1 minute for $1 per hour

Paid 35 · 13,099 votes

Thegist

general

Summarize Slack threads and channels

Paid 27 · 210 votes

Because this category covers so many domains, browsing by sub-use case is more efficient than scrolling the full list. Tools like Hippo Scribe and SopCreator serve very specific professional workflows, while others like User Evaluation or Userpersona target product and UX teams. The quality bar across the category is uneven: some tools are mature products with enterprise customers, while others are early-stage experiments. When evaluating any tool in this space, look for evidence of actual accuracy and reliability in your specific domain, since ML performance varies dramatically across tasks. Integration depth and data handling are often the deciding factors for business use. Pricing models are diverse, from usage-based API billing to flat-rate SaaS subscriptions. Open-source alternatives exist for many of the underlying tasks, so for teams with technical resources, comparing commercial tools against self-hosted options is worth the effort.