Informatique🌐 EN
Raider
#games & comics#informatique
raider.io
📄 Full details →
👥 Target audience
Joueurs de jeux vidéo
🌍 Target countries
Monde
🗣️ Available languages
FREN
🔄 Alternatives
🔗 Visit RaiderWowheadIcy Veins
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 | Developers and organizations needing high-accuracy, deterministic structured data extraction from documents, images, audio or video | — | |
| 3 | Developers building AI agents that need to send/receive email, SMS, voice calls or iMessage | — | |
| 4 | AI development teams, enterprises and startups building agentic systems, code assistants and conversational AI | — | |
| 5 | Teams building RAG pipelines, AI research agents, lead enrichment and competitive intelligence tools | — | |
| 6 | AI/agent developers, startups and enterprises needing to safely execute AI-generated code | — | |
| 7 | AI/ML developers and enterprises (healthcare, supply chain, legal, fintech) needing browser automation for AI agents | — | |
| 8 | Teams building AI agents that take real actions against third-party SaaS APIs (GitHub, Slack, Stripe, Linear) | — | |
| 9 | AI engineering teams | Product teams with non-technical prompt editors | — | |
| 10 | AI/ML engineers | Data scientists | Platform teams | — | |
| 11 | ML engineers | Data engineers | Enterprises in finance, retail, government | — | |
| 12 | ML engineers | Data engineers | — |
AI model purpose-built for tasks that need a consistent, reliable answer every time — reading documents, classifying content, transcribing speech.
Gives AI agents their own email address, phone number and iMessage identity, so they can send, receive and act on real-world communication.
Cloud inference platform for running and fine-tuning open-source language models fast, without owning any GPUs.
Web scraping and crawling API that turns entire websites into clean, structured data ready for AI models to read.
Secure, disposable cloud sandboxes that let AI agents safely execute generated code without touching real production systems.
Cloud infrastructure of real, headless browsers that AI agents can control to browse, click and fill out forms like a human would.
Testing environment that gives AI agents realistic, stateful clones of GitHub, Slack, Stripe and other SaaS tools so bugs get caught before production.
Collaboration platform for AI teams to manage, test and monitor the prompts that power their LLM applications.
Serverless cloud platform that runs Python code, including AI model training and inference, on GPUs with sub-second startup and pay-per-second billing.
Managed feature store and AI lakehouse platform for building production machine-learning systems with millisecond-latency feature serving.
Open-source feature store that manages the machine-learning data teams use for both model training and real-time predictions.