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AI app builder that turns words into real coded mobile apps, sites and tools, with GPT-5 and 40+ integrations for makers.
Serverless platform for running and fine-tuning image, video, audio and 3D generative models via one fast API.
High-performance open-source vector database for production AI retrieval and RAG, for teams needing scale, hybrid search, or self-hosting.
Memory layer/OS that gives AI agents persistent, self-evolving long-term memory across sessions and platforms, with SOTA benchmarks.
Open-source AI coding agent for VS Code, JetBrains, CLI and cloud, with 500+ models at zero inference markup and BYOK.
No public pricing
No public pricing
Free trial available
- ✦Natural-language to coded apps
- ✦Mobile, web and tool generation
- ✦GPT-5 and 40+ integrations
- ✦Database, web search and image generation
- ✦Automated testing and error logs
- ✦Custom domains and code export
- ✦1,000+ generative model APIs
- ✦Serverless GPU inference engine
- ✦On-demand and dedicated GPU clusters
- ✦Model fine-tuning and custom deployments
- ✦Bring-your-own-weights and private endpoints
- ✦SOC 2 compliance and enterprise features
- ✦Hybrid dense and sparse vector search (BM25, SPLADE, miniCOIL)
- ✦Advanced metadata filtering applied during search traversal
- ✦Multivector support for multimodal retrieval
- ✦Reranking with score boosting and late-interaction models (ColBERT, MMR)
- ✦Flexible deployment: cloud, hybrid, private, or edge
- ✦Rust-based engine optimized for low-latency, high-scale search
- ✦Persistent, self-evolving agent memory (EverOS)
- ✦Multimodal retrieval and ingestion (mRAG)
- ✦Single-API storage of many file types
- ✦Skill and case-based learning
- ✦Temporal fact tracking
- ✦Personal memory hub (EverMe)
- ✦500+ AI models at zero inference markup
- ✦Bring-your-own-keys and local model support
- ✦MIT-licensed, fully open source
- ✦Works in VS Code, JetBrains, CLI and cloud
- ✦Agent modes (Code, Architect)
- ✦Parallel isolated worktrees
- ✦Slack code reviewer and gateway
- →Building apps without writing code
- →Prototyping products quickly
- →Adding AI and integrations to apps
- →Publishing apps to custom domains or the App Store
- →Adding image/video generation to an app
- →Running fast diffusion-model inference at scale
- →Training or fine-tuning custom generative models
- →Building retrieval-augmented generation (RAG) pipelines
- →Powering AI recommendation and semantic search systems
- →Enterprises needing on-prem or hybrid deployment for compliance
- →AI agent platforms needing fast contextual retrieval at scale
- →Giving AI agents long-term memory
- →Maintaining context across sessions
- →Coordinating multi-agent teams
- →Building personalized AI assistants
- →Writing and refactoring production code with AI
- →Planning features before implementation
- →Running agents across multiple IDEs and the CLI