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Google's AI coding assistant for code completion, generation, chat and review across IDEs and GitHub.
Automated AWS usage optimization platform giving engineers 150+ recommendations across 50+ services, averaging ~10% savings.
Google Labs experiment for building and sharing AI mini-apps from natural-language prompts, no coding required.
Full-stack observability platform with an AI SRE agent that detects, debugs, and auto-fixes issues across infra, apps, and users.
EU-hosted GPU server rental service offering bare-metal, GDPR-compliant machines pre-loaded with AI tooling like ComfyUI and OpenWebUI.
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- ✦AI code completion and suggestions
- ✦Natural-language code generation
- ✦In-IDE chat assistance
- ✦AI code review
- ✦IDE integrations (VS Code, JetBrains, etc.)
- ✦GitHub integration
- ✦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
- ✦Build AI mini-apps from natural-language prompts
- ✦Visual editor for prompt/tool workflows
- ✦Share created apps with others
- ✦No-code AI app prototyping
- ✦Infrastructure and application performance monitoring
- ✦Log monitoring with AI insights
- ✦Real user monitoring
- ✦OpsAI SRE agent for detection and auto-fix
- ✦Synthetic and browser testing
- ✦LLM observability
- ✦Hourly or monthly GPU rental across 13+ GPU tiers
- ✦One-click AI environment templates (ComfyUI, OpenWebUI/Ollama, Jupyter, vLLM)
- ✦Pause/freeze billing to cut idle costs
- ✦Full root SSH access with persistent NVMe storage
- ✦Published GPU and LLM inference benchmarks
- ✦EU-based, GDPR-compliant hosting
- →Speeding up coding with AI completions
- →Generating code from plain-language prompts
- →Getting in-editor help and explanations
- →Reviewing pull requests with AI
- →Understanding unfamiliar codebases
- →Cutting AWS spend automatically
- →Rightsizing over-provisioned resources
- →Scheduling idle resources off-hours
- →Giving DevOps in-console cost recommendations
- →Prototyping an AI workflow quickly
- →Sharing a custom AI mini-app
- →Automating a task with chained prompts
- →Monitor full-stack app and infra health
- →Debug incidents faster with AI
- →Correlate frontend and backend issues
- →Observe Kubernetes and cloud environments
- →Running local LLM inference or fine-tuning without buying hardware
- →Generating images with ComfyUI/Stable Diffusion on rented GPUs
- →EU businesses needing GDPR-compliant AI infrastructure
- →Hobbyists experimenting with open-source AI tools on a budget
- →Short-term GPU bursts for training or rendering