Informatique🌐 EN
Raider
#games & comics#informatique
raider.io
📄 Full details →
👥 Target audience
Joueurs de jeux vidéo
🌍 Target countries
Monde
🗣️ Available languages
FREN
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When an AI coding assistant suggests a change, it usually describes the edit in words or a diff — but something still has to take that description and correctly apply it to your real file, matching up the right lines without breaking the rest of the code. Doing that with a big, slow general-purpose AI model is overkill and often unreliable. Morph built a small, specialized model whose only job is applying code edits, fast and accurately, so coding agents can act instead of just suggesting. Morph's flagship product, Fast Apply, is a 7-billion-parameter model that merges AI-generated code edits into existing files at roughly 10,500 tokens per second with around 98% accuracy, priced at $0.80 per million input tokens. It's available as an MCP tool that plugs directly into Claude Code, Cursor and other MCP-compatible coding environments, and is used in production by companies including JetBrains, Vercel and Webflow. Beyond Fast Apply, Morph offers a small suite of related infrastructure for coding agents: WarpGrep for agentic codebase search, FlashCompact for context compaction at 25,000+ tokens/second, and Reflexes for agent behavioral observability. Pricing includes a free tier (200 requests/month, 250,000 credits worth about $2.50), with usage-based pricing beyond that scaling across all four products.
| # | Tool | Best for | Price |
|---|---|---|---|
| 1 | Joueurs de jeux vidéo | — | |
| 2 | Enterprise customers, SaaS developers and voice-agent builders needing phone-based AI agents | — | |
| 3 | Enterprise organizations and foundation model builders needing multimodal data annotation | — | |
| 4 | AI developers, researchers and companies training and serving ML models without long procurement cycles | — | |
| 5 | Enterprises in fintech, healthcare and hospitality needing natural, multilingual conversational voice AI | — | |
| 6 | Support and sales teams in healthcare, financial services, insurance, logistics, retail and hospitality | — | |
| 7 | Hyperscalers, regulated enterprises, frontier AI labs, startups, researchers and government | — | |
| 8 | Frontier AI labs, research teams and enterprises building AI agents and robotics systems | — | |
| 9 | Data scientists and AI/ML teams running multiple large-scale annotation projects in parallel | — | |
| 10 | Computer vision and physical AI/robotics teams needing to label video, 3D/LiDAR and multi-sensor data | — | |
| 11 | Developers building voice AI applications, platforms embedding speech APIs, enterprises with custom model needs | — | |
| 12 | Enterprise AI labs and research organizations needing large-scale, dedicated NVIDIA GPU capacity | — |
Developer platform that wires together speech recognition, an AI model and speech generation into a working phone-answering voice agent.
Data annotation and evaluation platform that turns raw images, video, text and audio into labeled datasets for training and fine-tuning AI models.
Pay-by-the-second GPU cloud for training and running AI models, with no contracts and fast serverless cold starts.
Text-to-speech API built by linguists for hundreds of natural-sounding voices across 50+ languages, tuned for real conversation, not audiobooks.
No-code-friendly platform for building AI phone agents that handle customer service and sales calls, with drag-and-drop configuration.
GPU cloud built for AI research and production, scaling from a single rented GPU up to superclusters with over 165,000 GPUs.
Data platform for labeling, curating and generating human feedback to train and fine-tune AI models, including reinforcement learning workflows.
Data annotation platform built for organizations running many labeling projects at once across images, video, text, PDF and geospatial data.
Platform for labeling, organizing and quality-checking the images, video and sensor data used to train computer vision and robotics AI models.
Speech recognition and voice-generation API that lets developers add accurate, fast transcription and natural-sounding speech to any app.
Enterprise cloud built specifically around NVIDIA GPUs, providing large-scale compute for training and running the biggest AI models.