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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.
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Browse TikTok and Meta ads to find winning creatives
Real-time speech translation with AI voices
Free AI sound effect generator from text
SEO-optimized blog posts from real data
Generate short videos from text prompts
Generate essays with real citations in seconds
Chat interface to automate tasks in apps
Record and share video messages
Transform images into videos with AI
Convert text to audio with natural voices
AI video editor with auto-transcription
Generate royalty-free music across multiple styles
Rewrite AI-generated text to avoid detection
Convert AI-generated text to read as human-written
Generate 3D character animations from text descriptions
SEO-optimized blog posts generated in minutes
Code context management for AI coding
Convert AI-generated Spanish text to human-like writing
Generate dating app reply options instantly
Check for AI content and remove detection markers
Copywriting tool with advanced formatting and styling
Generate original music, vocals, and lyrics from text
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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.