Telborg
generalDaily data on US energy, power grids, and permits
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.
Daily data on US energy, power grids, and permits
Converts presentations to text notes
Auto-generate step-by-step guides
ChatGPT app for iPhone, iPad, and Mac with Siri integration
Generate buyer personas and convert features into benefits
Generative AI transformations for batch image editing
Summarize text, articles, PDFs, and videos in 50+ languages
Business AI assistant
Directory of new Australian casinos
Knowledge bases
Extract data from receipts with OCR and AI
Virtual AI clones
Practice coding interviews with AI hints and feedback
AI-powered tool for fast, accurate book translation for authors and publishers
Screen short-term rental guests with AI
Android chat app with multiple AI models and voice support
Summarize Slack threads and channels
QR code generation with AI
AI-powered threat intelligence collection and analysis
Learning resources for large language models and AI fundamentals
AI-powered chat summaries for LiveChat conversations
Search and book travel directly from ChatGPT
Research and experiments in safe artificial intelligence from DeepMind
AI-powered podcast search and discovery platform
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.