Colossyan Creator
generalCreate videos with AI actors
llms 21
This category covers tools built around large language models: infrastructure for deploying, fine-tuning, evaluating, and monitoring LLMs in production. With 369 tools listed, it is one of the more technical categories on the site, aimed primarily at developers and ML engineers rather than end users.
Lara Translate
generalFast translations across multiple languages
RegexMy
generalAI regex generator and tester
Picture To Text Converter
generalExtract text from images, PDFs, and handwritten notes
Omnipilot
generalAutomate workflows across macOS apps
Free Humanize AI Content
generalConvert AI text to human-sounding content for free
Xpeacho
generalConvert text to human-sounding voiceovers for videos
Txt Muse
generalWriting tools for brainstorming, drafting, and copy refinement
Dorascribe
generalAI medical documentation for clinical notes
Lunchbreak AI
generalHumanize AI text to pass detection
OK9
generalContent and code generation platform
LilysAI
generalSummarize videos, audio, PDFs, and websites
Story Diffusion Gen
generalGenerate consistent images and videos from text
Memenome
generalStudy complex topics through your favorite characters and memes
CAMBIADOR DE PALABRAS
generalRewrite text in Spanish and remove plagiarism
ChatGPT Notepad
generalFree online notepad for quick note-taking and organization
Solace
generalDocument summarization and Q&A
Nexform
generalBuild forms from ideas using AI
Data Science in Libraries
generalData science programs in libraries
Soundify
generalGenerate sound effects for videos and memes with AI
Picture Translate
generalFree online tool that translates text from images to English or other languages
LLM tooling has exploded alongside the models themselves, and the category now spans several distinct problem areas. Deployment and serving tools like PeriFlow and Dstack help teams run models efficiently at scale. Evaluation and observability tools like UpTrain and AIWatch track model quality, drift, and cost over time. Memory and retrieval tools like Cognee add persistent context or RAG capabilities to LLM applications. When choosing, the key questions are infrastructure fit (cloud, on-prem, or hybrid), model compatibility (OpenAI-only vs. open-weight models), and whether the tool addresses your actual bottleneck, whether that is latency, cost, accuracy, or developer velocity. Pricing structures vary: some tools charge per token processed, others per seat or per API call. Open-source options exist across most sub-categories, which is worth considering for teams with engineering capacity to self-host.