Prompt Selected
generalBrowser extension for AI-powered text tasks
General LLM tools include frameworks, APIs, evaluation utilities, and infrastructure specifically built around large language models. This category covers 369 tools that help developers build, test, fine-tune, and run applications on top of LLMs, from embedding calculators to full model-serving platforms.
Browser extension for AI-powered text tasks
Humanize AI writing to sound natural
Guide to using AI tools for content creation
Extract text from images and scanned documents
Speech to text for emails and documents on macOS
Live soccer scores and match schedules
Email client as simple as text messaging
Free text to speech with natural-sounding voices
Free online tool that translates text from images to English or other languages
Converts and formats AI-generated text for readability and usability
AI photo studio that creates professional product photos from simple images
AI video generator that creates realistic videos from text and image prompts
Convert handwritten documents to digital text
Convert text and images to professional videos
Convert handwritten notes to searchable text
Shorten text while preserving meaning and voice
Generate blog posts and social media content
Feature flagging with rollout controls and auto-rollback
Website hosting and blogging service
One-tap clipboard manager for Apple devices
Web platform for creating with AI models
AI writing tool for marketing copy and blogs
Headless CMS for Next.js applications
Free text-to-speech synthesis with natural speech
This is a technically focused category aimed primarily at developers and ML engineers. Tools like Cognee and UpTrain address retrieval-augmented generation (RAG) pipelines and model evaluation, while platforms like Dstack and PeriFlow handle compute infrastructure for training and inference. Embedding Similarity Calculator and similar utilities fill narrow but useful gaps in LLM development workflows. OpenAssistant and Cerebras-GPT represent open-source or open-weight models that developers can run or fine-tune directly. When comparing options, consider whether a tool is model-agnostic or tied to a specific provider, and whether it supports the models you are already using. Latency, throughput, and cost-per-token are the metrics that matter most for production workloads. Evaluation tools are often underinvested in early projects but become critical once you are shipping to users. Many tools here are open source with paid managed versions, while others are closed SaaS products with usage-based pricing.