Deploy AI agents
as production services
Run agents up to 100x cheaper.
Deploy any Python agent in one click with automatic scale up and scale down, built-in security, hosted memory, and zero vendor lock-in.
Maintain complete ownership of your code with no vendor lock-in. Package with open-source dank-py and deploy with Dank Cloud.
Open Source & Ownership
Keep full ownership of your agent code
Dank Cloud is built on an open-source packaging engine and keeps your deployment model portable. Use our managed platform for speed, while preserving the flexibility to run your packaged agents anywhere.
Open-source runtime
Delta-Darkly/dank-py
Portable artifacts
Container-first packaging keeps deployment options open.
No lock-in
Your source code and runtime contract stay under your control.
Elastic by default
Scale up on demand and scale down when traffic cools.
Secure runtime
Isolated agents with encrypted secrets and endpoint auth.
Framework Agnostic
Build with any agent framework
Dank Cloud supports framework and framework-free Python agents through one universal invocation contract. Deploy and operate them the same way no matter how they are built.
Custom PythonSupported
LangChainSupported
AutoGenSupported
PydanticAISupported
HaystackSupportedCustom PythonSupportedLangChainSupportedAutoGenSupportedPydanticAISupportedHaystackSupportedCustom PythonSupportedLangChainSupportedAutoGenSupportedPydanticAISupportedHaystackSupportedCustom PythonSupportedLangChainSupportedAutoGenSupportedPydanticAISupportedHaystackSupported
LlamaIndexSupported
CrewAISupported
DSPySupported
LangGraphSupported
MastraSupportedLlamaIndexSupportedCrewAISupportedDSPySupportedLangGraphSupportedMastraSupportedLlamaIndexSupportedCrewAISupportedDSPySupportedLangGraphSupportedMastraSupportedLlamaIndexSupportedCrewAISupportedDSPySupportedLangGraphSupportedMastraSupportedUniversal Python Runtime
Available now
Deploy LangChain, LangGraph, CrewAI, and custom Python agents through one standardized deployment and invocation path.
Start FreeOpen Source, No Lock-In
Built on dank-py
Keep full ownership of your code and packaging workflow through the same standardized runtime contract, with full portability over your deployment artifacts.
View GitHubQuick Start
Deploy in 3 steps
From GitHub repo to production endpoint in under 5 minutes
Connect GitHub
Connect your GitHub repo in one click. Dank Cloud detects your agents and their configuration automatically.
Configure
Select which agents to deploy. Set environment variables, secrets, and resource allocation. Everything is configurable from the dashboard.
Deploy
Click deploy. Each agent launches as its own secure, API-addressable service in seconds.
Platform Features
Everything you need to ship agents
We handle the annoying scalable infrastructure—deployment, routing, auth, logs, memory—so you can focus on building great agents.
Agent Management
Full control over every agent
Manage every aspect of your deployed agents through an intuitive dashboard. Monitor performance, configure resources, and optimize utilization in real-time.
Resource allocation
Set CPU, memory, and instance size per agent. Scale resources based on workload requirements.
Real-time monitoring
Track agent status, uptime, and health metrics. Know exactly when something needs attention.
One-click actions
Start, stop, restart, or redeploy agents instantly. Full lifecycle management from the dashboard.
Available Endpoints
GET /healthGET /metricsPOST /promptExample Request
curl -X POST "https://<agent-id>.ai-dank.xyz/prompt" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer <YOUR_API_KEY>" \
-d '{"prompt": "Explain how transformers work."}'Dedicated Endpoints
Each agent gets its own domain
Deploy and go straight to production with stable, agent-specific endpoints. Each agent is instantly accessible via its own dedicated HTTPS URL.
Instant production URLs
Every agent gets a unique subdomain. No DNS configuration required.
SSL/TLS by default
All endpoints are secured with HTTPS automatically. No certificate management needed.
Direct HTTP access
Call agents directly via REST API. No routing configuration or gateway setup.
Observability
Per-agent logs and visibility
Clear, isolated logs for each agent. See exactly what each agent is doing, when it fails, and why. No more digging through mixed backend logs.
Isolated log streams
Each agent has its own dedicated log stream. Filter and search per-agent.
Real-time streaming
Watch logs as they happen. Debug issues immediately during development.
Tracing
End-to-end request tracing across agent calls in multi-agent workflows.
Integrations
Powerful integrations, zero setup
Connect your tools and services seamlessly. We've built deep integrations so you don't have to.
GitHub Integration
Push to deploy, automatically
Connect your GitHub repository and get full CI/CD out of the box. Every push to your branch triggers an automatic rebuild and redeployment.
Auto-redeployments
Push to your branch, agents redeploy automatically. Zero manual deployment steps.
Fast builds
Optimized Docker builds complete in seconds. Get from code to production faster.
Build logs
Real-time build output and deployment history. Debug build failures instantly.
Vector Memory
Built-in memory for your agents
Every agent comes with a production-ready vector store out of the box. Store and retrieve memory, embeddings, and context without provisioning or operating a database.
Vector storage
Store embeddings for RAG, semantic search, and long-term agent memory.
Fast similarity search
Query vectors with low latency. Weaviate handles indexing automatically.
No setup required
Pre-configured and ready to use. Just connect from your agent code.
MCP Deployment
Offload tools and heavy compute to MCP services
Keep agent containers lean by deploying shared tools and high-compute integrations as dedicated MCP services. This separation improves isolation, scalability, and cost efficiency under real traffic.
Dedicated tool plane
Run shared tools once and let multiple agents invoke them safely.
Lighter agent runtimes
Keep core agents focused on reasoning while MCP services handle heavy lifting.
Composable architecture
Build distributed AI systems with clear service boundaries and cleaner observability.
Security
Built-in authentication & secrets
Secure your agents with API keys and encrypted secrets. No custom auth or credential plumbing required.
API key management
Generate and manage API keys per agent. Control who can access each endpoint.
Secrets management
Store API keys, tokens, and credentials securely. Secrets are encrypted at rest and injected into agents at runtime.
Environment variables
Set environment variables in the dashboard. Apply changes on deploy, no code changes required.
Architecture
Each agent runs independently
Most platforms run all agents in a shared runtime. Dank deploys each agent as its own service, so failures are isolated, scaling is elastic, and logs are clear.
Shared Fate
All agents share one runtime. One crash kills all. Limited visibility makes debugging harder.
Scaling Requires Restart
When one agent needs more resources, you must shut down everything and redeploy.
No Way to Scale Down
Once upgraded, you're stuck paying for oversized specs even when traffic cools.
Isolated Failures
Each agent runs in its own container. If one crashes, the others keep running. Auto-restart in the background.
Elastic Scaling
Each agent automatically scales independently based on load. Scale up when hot, scale down when idle. Pay only for what you use.
Built-in Routing & Tracing
Requests are automatically routed to available agents to distribute load. Trace every step of multi-agent requests end-to-end.
Pricing
Simple tier pricing with usage-based overage
Every request counts as one request. Time above 30 seconds is metered as overtime seconds. Free includes cold starts. Plus and Pro remove cold starts.
Free
Great for experimentation
$0
per month
Plus
Production-ready usage
$25
per month
Pro
High-throughput deployments
$99
per month
Pay-as-you-go overage pricing
Ready to deploy?
Deploy stateless agent microservices with the economics, security, and flexibility required for production.