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Unified API gateway to 500+ AI models (GPT, Claude, Sora, image/video) with OpenAI-compatible endpoints and discounted usage.
Search, crawling and research API built for AI agents, with token-efficient results and structured web-data enrichment.
Lightweight MIT-licensed JavaScript chatbot UI widget for building support-agent chat interfaces on top of any LLM.
Automated AWS usage optimization platform giving engineers 150+ recommendations across 50+ services, averaging ~10% savings.
Developer tool that deploys Docker Compose apps (with LLMs and databases) into your own AWS, GCP or Azure account via one command.
No public pricing
No public pricing
Free trial available
- ✦Single OpenAI-compatible API for 500+ models
- ✦Chat, image, video and audio models
- ✦Discounted per-request pricing
- ✦One dashboard for keys, quotas and usage
- ✦Multi-region routing and failover (99.9% uptime)
- ✦Multiple payment methods incl. crypto
- ✦Web search API tuned for agents
- ✦Full-page contents with token-efficient highlights
- ✦Asynchronous agents for deep research and enrichment
- ✦Structured outputs with grounded citations
- ✦Web monitors that track new events on a schedule
- ✦Zero data retention and SOC 2 Type II controls
- ✦MIT-licensed and free to use
- ✦Lightweight (~65kb) JavaScript widget
- ✦4 message display modes plus typewriter effect
- ✦Markdown support and chat history
- ✦Backend hook to integrate any LLM
- ✦Responsive, mobile-friendly, read-only mode
- ✦150+ recommendations across 50+ AWS services
- ✦Zombie and unused resource cleanup
- ✦Over-provisioned rightsizing
- ✦Idle-resource scheduler
- ✦SpotBot for ECS Fargate spot/on-demand switching
- ✦AWS console extension with Slack/Teams alerts
- ✦One-command deploy from Docker Compose
- ✦Deploys into your own or a customer's cloud account
- ✦Native managed LLM access (Bedrock/Vertex/Azure AI)
- ✦Managed Postgres, MongoDB and Redis
- ✦Auto-configured IAM, VPC, TLS and load balancing
- ✦Open-source CLI and cloud providers
- →Accessing many AI models via one API
- →Cutting AI model API costs
- →Building multimodal AI apps
- →Consolidating AI billing and keys
- →Give coding agents current docs and repo context
- →Power chatbots with real-time web answers
- →Enrich company and people data at scale
- →Monitor the web for fresh events
- →Adding an AI chat UI to web apps
- →Building LLM-powered support agents
- →Embedding chat widgets in existing products
- →Prototyping chatbot interfaces
- →Cutting AWS spend automatically
- →Rightsizing over-provisioned resources
- →Scheduling idle resources off-hours
- →Giving DevOps in-console cost recommendations
- →Shipping AI agents and web apps to production
- →Deploying the same app across many customer clouds
- →Agencies deploying into client cloud accounts
- →Avoiding hand-written Terraform or Kubernetes