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General-purpose autonomous AI agent that plans and runs multi-step tasks such as building sites, slides and research in the cloud.
AI super-assistant plus enterprise ML platform: ChatLLM for teams and end-to-end model building for enterprises; broad, pricing not shown.
LLM observability platform and AI gateway that lets teams route, log, debug and analyze their model requests.
Open-source AI-agent observability platform for tracing sessions, clustering failures and running evals on live traffic.
No public pricing
No public pricing
Free trial available
No public pricing
No public pricing
- ✦Autonomous multi-step task execution
- ✦Website and app building
- ✦AI slides, design and image generation
- ✦Manus browser operator
- ✦Wide Research mode
- ✦Cross-platform web, desktop and mobile apps
- ✦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
- ✦Request logging and LLM observability
- ✦AI gateway with routing and automatic fallbacks
- ✦Caching and rate limiting
- ✦Session, user and custom-property analytics
- ✦Prompts, playground and datasets for testing
- ✦Integrations with OpenAI, Anthropic, Azure and more
- ✦Open-Source AI Gateway
- ✦Multi-LLM Management & Cost Optimization
- ✦Efficient and Secure LLMs Invocation
- ✦Unified API Signature for LLMs
- ✦Load Balancer for seamless switching between LLMs
- ✦Fine-Grained Traffic Control for LLMs
- ✦LLM Quota Management
- ✦Real-time LLM Traffic Monitoring
- ✦Caching Strategies for AI in Production
- ✦Flexible Prompt Management
- ✦Agent trace capture and conversation intelligence
- ✦Semantic and exact-text search across all traces
- ✦Automatic issue discovery with Slack/email/webhook alerts
- ✦OpenTelemetry-compatible SDK with no lock-in
- ✦Automated evals and golden dataset generation
- ✦Failure-mode clustering and MCP server integration
- →Automate end-to-end digital tasks
- →Produce websites and presentations
- →Conduct broad research
- →Hand off browser tasks to an agent
- →Chat with many AI models in one place
- →Build and deploy ML models
- →Automate tasks with AI agents
- →Monitoring and debugging LLM apps
- →Analyzing model usage and cost
- →Caching responses to cut spend
- →Managing prompts and testing datasets
- →Building API portals for secure sharing of internal APIs with partners.
- →Tracking API usage and driving API monetization.
- →Managing and securing API access in compliance with enterprise policies.
- →Connecting to multiple AI large models simultaneously.
- →Optimizing LLM costs and improving efficiency.
- →Protecting against LLM attacks and data leaks.
- →Monitoring AI agents in production
- →Debugging and triaging agent failures
- →Building regression evals from real traffic
- →Getting alerted on new or escalating issues