Plusdocs
generalAI presentation maker for PowerPoint and Google Slides
General AI and machine learning tools include platforms for building, deploying, and managing ML models, along with infrastructure, evaluation, and workflow tools that support AI development broadly. With 674 tools, this category covers a wide spectrum from no-code ML builders to developer-facing MLOps infrastructure.
AI presentation maker for PowerPoint and Google Slides
Automate deal analysis and CIM review
Press kit creation and media distribution
AI note-taking for students and researchers
Transcribe and translate video content
Autonomous PR agent that pitches journalists and books podcasts
AI chat bot for Twitch and Kick with custom personalities and games
AI essay, email, and script writing
ChatGPT-powered content generation for WordPress
Use AI anywhere on Mac with keyboard shortcuts
Automated code review for bugs, security, and performance
AI writing assistant for lesson planning, grading, and quizzes
Summarizes text, PDFs, URLs, and articles in seconds
Automatically generates Gmail replies in your voice and style
Discounted hotel, apartment, and villa bookings
Video translation, dubbing, and voiceovers in 75+ languages
Travel blogging platform where you can earn crypto
Online lottery platform
ChatGPT prompt templates for SEO, marketing, and business
ChatGPT browser extension for every website
This category includes tools aimed at very different audiences. Platforms like Ultracode and Workverse lean toward automation and productivity applications built on AI, while infrastructure tools like EdgeTrace serve engineers managing model pipelines and monitoring production systems. Tools like Userpersona and Hippo Scribe apply ML techniques to specific tasks like persona generation or medical transcription. The unifying thread is that they are powered by machine learning but do not fit neatly into a narrow vertical like image generation or speech-to-text. When navigating this category, the most useful filters are technical depth (no-code vs. API-first), deployment environment (cloud vs. self-hosted), and target use case. Many enterprise-grade tools here require custom pricing quotes, while developer tools often offer usage-based billing. Evaluating model accuracy and latency on your specific data is almost always necessary before committing to production use.