Yesterday’s Top Products

Transcribe interviews and recordings, edit speaker-labelled text, and export transcripts or subtitles.

Create and study flashcards from notes, PDFs, slides, and other class material, with optional premium AI features.

Enhance, upscale, caption, and edit short videos in Vmake Labs, with daily free limits and larger paid allowances.

A general-purpose AI agent for multi-step research, documents, slides, and web or app tasks.

A browser-based assistant powered by Z.ai’s GLM models, with chat and agent-style capabilities.

Alibaba’s Qwen assistant for everyday chat and multimodal tasks, distinct from deploying Qwen models through an API.

Moonshot’s AI assistant for search, long documents, research, chat, and agent tasks, with separate developer access.

Google’s AI creative workspace for making video scenes and working with image and video generation tools.

Turn text into editable diagrams and presentation visuals, then export the result for documents or slides.

A creative suite for AI image, video, audio, editing, and upscaling workflows, including the former Freepik AI tools.

Create AI video and image assets in a visual workspace, with a separate developer API for model access.

Translate text and documents, refine writing, and add language workflows through paid plans or an API.

Low-latency speech generation, speech recognition, and voice-agent tools for developers and teams.

Audio intelligence APIs for transcription, streaming speech, speaker labeling, and voice-agent applications.

Speech-to-text, text-to-speech, and voice-agent APIs for applications that process or generate spoken audio.

Run Python functions, model inference, and GPU jobs on serverless infrastructure that scales with demand.

Host and call open models through an inference platform with serverless APIs, dedicated deployments, and tuning options.

Run supported AI models through Cloudflare’s serverless GPU network from Workers or the Cloudflare API.

Build and operate AI applications on Google Cloud with Gemini, Model Garden, tuning, evaluation, and managed deployment services.

Microsoft’s environment for selecting, deploying, evaluating, and governing models and AI agents on Azure.

Use foundation models from multiple providers through AWS, with managed knowledge, agent, and governance services.

A Python-based visual builder for AI applications, agents, retrieval flows, and MCP-connected tools.

Visually assemble language-model chains, retrieval pipelines, and AI agents, then expose them through applications or APIs.

Build and deploy model-backed apps and agent workflows with a visual interface, knowledge sources, and API access.

A developer-focused search database for vectors, documents, and metadata, with local and hosted deployment options.

Open-source and managed AI database for vector, keyword, and hybrid search across application data.

Vector search infrastructure for semantic retrieval, recommendation, and AI applications that need filtered nearest-neighbor search.

Build repeatable image and video generation workflows by connecting models and processing steps in a node graph.

A self-hosted interface for local and hosted models, with document search, tools, users, and shared AI workspaces.

Explore and run local language models in a desktop app, with an optional hosted-model service and a local developer endpoint.