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Enterprise AI coding assistant that pulls context from an entire codebase to power chat, code edits and debugging.
Agentic AI platform ('Aiden') that automates incident response, infrastructure-as-code and observability tasks with policy-based governance.
Documentation platform for publishing accurate, AI-ready docs sites, with Git sync and an MCP server for AI tools.
EU-hosted GPU server rental service offering bare-metal, GDPR-compliant machines pre-loaded with AI tooling like ComfyUI and OpenWebUI.
Cloud-agnostic AI/ML workflow orchestrator that runs pipelines inside a customer's own infrastructure for compute-heavy teams.
No public pricing
No public pricing
Free trial available
- ✦Codebase-aware developer chat
- ✦AI code completions and inline edits
- ✦Customizable and shareable prompts
- ✦Automatic bug identification and debugging help
- ✦Context filters to exclude sensitive repos
- ✦Integrates with major code hosts and IDEs
- ✦Automated service discovery and dependency topology mapping
- ✦SLO-based alert triage and prioritization
- ✦AI-driven root cause analysis with pre-built workflows
- ✦Human-approved remediation with full audit trails
- ✦Works alongside existing tools like Datadog, Grafana, New Relic
- ✦Governance and policy enforcement layer for agent actions
- ✦Publish structured documentation sites
- ✦Git sync for docs-as-code workflows
- ✦AI setup agent to build and import docs
- ✦GitBook MCP server for AI access
- ✦Enterprise controls
- ✦Free tier to start
- ✦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
- ✦Python-native dynamic workflow authoring
- ✦Automatic failure recovery, caching, and versioning
- ✦Zero Trust architecture keeping data inside customer's cloud
- ✦Real-time inference and agentic-AI workflow support
- ✦High-throughput scaling (tens of thousands of actions per run)
- ✦Local development environment matching production behavior
- →Engineers asking questions about an unfamiliar large codebase
- →Teams standardizing common coding tasks with shared prompts
- →Developers debugging errors faster with AI-assisted context
- →Enterprises running large-scale code migrations
- →SRE teams reducing mean-time-to-resolution during incidents
- →Platform engineers wanting policy-governed AI infrastructure management
- →Enterprises needing SOC 2 / PCI / HIPAA-compliant AI operations
- →Publish product and API documentation
- →Maintain docs-as-code with Git sync
- →Make docs consumable by AI assistants
- →Import existing docs into a hosted site
- →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
- →ML teams orchestrating training and inference pipelines at scale
- →Biotech/geospatial companies needing GPU-heavy pipeline orchestration
- →Enterprises migrating off Airflow for ML workflow management
- →Teams requiring workflows that never send data outside their own cloud