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AI super-assistant plus enterprise ML platform: ChatLLM for teams and end-to-end model building for enterprises; broad, pricing not shown.
Unified API and gateway routing requests across 200+ models from 40+ providers, with cost tracking and a free BYOK tier.
Credit-based AI coding agent that builds full applications from plain-language instructions, including backend, billing, and admin features.
Open-source platform to build, deploy and monitor agentic AI workflows and RAG apps, with cloud, self-host and enterprise options.
No public pricing
No public pricing
Free trial available
Free trial available
- ✦ChatLLM access to multiple top AI models
- ✦AI agents and automation
- ✦No-code full-stack app creation
- ✦Enterprise generative AI platform
- ✦Structured ML model building
- ✦Optimization and forecasting
- ✦Dialogue with GLM large model
- ✦AI search
- ✦AI drawing
- ✦AI reading
- ✦AI-generated video (沉思清影-AI生视频)
- ✦AI-generated PPT
- ✦Data analysis tools
- ✦Code assistance (代码速写)
- ✦Intelligent agents
- ✦One API for 200+ models across 40+ providers
- ✦Provider switching without code changes
- ✦Real-time cost tracking
- ✦Bring-your-own-keys, free forever
- ✦Observability and guardrails
- ✦SOC 2 Type II certified
- ✦Builds complete apps (auth, storage, payments, admin) from natural-language prompts
- ✦Runs on top of multiple frontier coding models
- ✦Retains full project context across sessions for incremental feature additions
- ✦Remote task submission via Slack/Telegram messaging
- ✦'Eco Mode' for lower-cost usage without consuming credits
- ✦VS Code and JetBrains IDE integrations plus a desktop app
- ✦Visual workflow studio for agents
- ✦RAG knowledge pipelines
- ✦Agent runtime with tools and memory
- ✦Marketplace of models and plugins
- ✦Publish as app, API or MCP tool
- ✦Logging, analytics and monitoring
- →Chat with many AI models in one place
- →Build and deploy ML models
- →Automate tasks with AI agents
- →Engaging in conversations with an AI model
- →Generating images and videos using AI
- →Creating presentations with AI assistance
- →Analyzing data with AI tools
- →Assisting with code development
- →Route across many LLM providers from one API
- →Track and control AI spend
- →Avoid vendor lock-in with provider switching
- →Solo founders building a launchable product without a dev team
- →Developers offloading multi-step feature builds to an autonomous agent
- →Teams wanting a shared coding agent with pooled usage billing
- →Building AI agents and chatbots
- →Creating RAG-based knowledge apps
- →Deploying LLM apps at enterprise scale