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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.
Pay-per-use API hub aggregating 1000+ image, video, and audio generation models for developers building AI media pipelines.
Anthropic's AI assistant for writing, coding, and analysis across web, mobile, and desktop, plus a developer API.
General-purpose autonomous AI agent that plans and runs multi-step tasks such as building sites, slides and research in the cloud.
Unified API gateway that routes requests to 400+ LLMs across 70+ providers with failover and no subscription.
Free trial available
No public pricing
- ✦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
- ✦Unified API access to 1000+ image/video/audio generation models
- ✦Pay-per-use pricing billed per image or per second of video
- ✦Includes chat/LLM model access (Claude, GPT, Gemini, etc.) priced per token
- ✦Account tiers unlock higher GPU limits and concurrency
- ✦CLI and desktop app for building workflows
- ✦Enterprise options with dedicated support and custom deployment
- ✦Conversational writing and editing
- ✦Code generation and debugging (Claude Code)
- ✦Data analysis and visualization
- ✦Web search plus memory across chats
- ✦Connectors and remote MCP integrations
- ✦Extended thinking for complex tasks
- ✦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
- ✦One unified, OpenAI-compatible API for 400+ models
- ✦Automatic provider failover for higher uptime
- ✦Edge routing for low latency
- ✦Custom data and provider policies
- ✦Pay-as-you-go credits usable across any model
- →Turning prompts into maintainable, spec-matched code
- →Catching bugs unit tests miss
- →Reviewing PRs and fixing bugs in CI/CD
- →Integrating AI image/video generation into an app via API
- →Building automated content pipelines needing multiple AI models
- →Testing and comparing many generative models from one account
- →Scaling AI media production with volume-based account tiers
- →Accessing both media-generation and LLM APIs from one platform
- →Drafting and refining written content
- →Building and debugging software
- →Analyzing datasets for insights
- →Research and learning support
- →Team and enterprise automation
- →Automate end-to-end digital tasks
- →Produce websites and presentations
- →Conduct broad research
- →Hand off browser tasks to an agent
- →Accessing many LLMs through one integration
- →Adding provider redundancy to AI apps
- →Comparing model price and performance
- →Powering agents and AI-native products