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No-code visual builder to create, deploy and orchestrate AI agents across 200+ models, for individuals to enterprise.
Fast, low-cost AI inference provider running LLMs on custom LPU chips via GroqCloud's pay-as-you-go API.
Kiro is a spec-driven agentic coding tool for IDE, CLI and web that turns prompts into specs and catches bugs with property-based tests.
General AI agent that executes multi-step tasks end to end — research, slides, design, browsing — instead of only answering questions.
Agentic AI platform with a coding desktop app, CLI, and cloud agents for autonomous software development and office work.
No public pricing
No public pricing
Free trial available
- ✦No-code visual agent builder
- ✦200+ AI models via service router
- ✦100+ prebuilt templates
- ✦Agent skills, plugins and workflows
- ✦AI Media Workbench for video/image
- ✦Enterprise controls (SSO, permissions, self-host)
- ✦LPU custom inference hardware
- ✦GroqCloud tokens-as-a-service API
- ✦High-speed, low-latency inference
- ✦Pay-as-you-go token pricing
- ✦Free API key to start
- ✦Broad open-model support
- ✦Spec-driven development (requirements, design, tasks)
- ✦Parallel agents, local or cloud
- ✦Property-based and correctness testing
- ✦Works in IDE, CLI, web and mobile
- ✦Multiple models (Claude, open-weight, Auto)
- ✦Headless CLI for CI/CD
- ✦Context from tools like Figma and Terraform
- ✦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
- ✦Multi-agent collaboration for end-to-end tasks
- ✦Persistent memory and custom rules
- ✦Extensible skills and plugins
- ✦Rich context across code, images, and directories
- ✦Automatic codebase documentation generation
- ✦Terminal-native CLI and JetBrains IDE plugin
- ✦Cloud-hosted agents for enterprise use
- →Automating business workflows
- →Building custom AI agents without code
- →Content and media generation
- →Deploying agents across a team or org
- →Running LLM inference at high speed
- →Cutting inference costs at scale
- →Powering low-latency AI chat apps
- →Serving models via a hosted API
- →Turning prompts into maintainable, spec-matched code
- →Catching bugs unit tests miss
- →Reviewing PRs and fixing bugs in CI/CD
- →Automate end-to-end digital tasks
- →Produce websites and presentations
- →Conduct broad research
- →Hand off browser tasks to an agent
- →Autonomous feature development in large codebases
- →Terminal-based AI pair programming
- →Cross-department task automation for legal, finance, HR
- →Onboarding developers to unfamiliar codebases