Unlike static agent builders, Skymel OA creates agents at runtime that adapt their entire workflow per request. Build agents from prompts that reason globally, optimize across cost/speed/quality, and route seamlessly between cloud and edge—automatically.
# Create agent from simple description
from skymel import OrchestratorAgent
agent = OrchestratorAgent(
description="Customer support agent that researches issues
and provides solutions",
budget=5.00
)
# Agent plans and executes automatically
result = await agent.run(
"Customer says their premium subscription isn't working"
)
print(result.solution)ARIA demonstrates Skymel OA's autopilot capabilities—creating agents that plan, adapt, and execute complex workflows from simple prompts, in real time.
Experience live AI orchestration
Understanding the fundamental difference in how Skymel OA approaches AI orchestration
Agents that adapt their behavior based on input, but require pre-defined structure:
Agents created entirely from scratch at execution time:
"Compare top 3 health insurance plans in California for freelancers"
Limited by pre-built tools and fixed workflow structure
"Compare top 3 health insurance plans in California for freelancers"
Agent structure, tools, and logic built specifically for this request
Skymel OA supports both fully automatic runtime agent creation AND dynamic agents with developer control, giving you the flexibility to choose your level of orchestration.
Just describe your goal. OA creates the entire agent from scratch.
agent = oa.run("Analyze competitor pricing and write a report")
# OA builds tools, plan, execution automatically
Perfect for rapid prototyping and high-level automation
Set constraints and tools. OA optimizes within your parameters.
agent = oa.run(
goal="Analyze competitor pricing",
allowed_tools=["web_scraper", "pdf_reader"],
max_cost=0.05
)
Ideal for production apps requiring specific control
As every company moves from single-model LLM demos to real AI-driven workflows and agentic apps, Skymel OA is the autopilot that makes it all possible: reliably, observably, and at scale.
Unlike traditional dynamic agents that adapt pre-built structures, Skymel OA creates the entire agent—plan, structure, tools, and model choices—from scratch at execution time based on your prompt and constraints.
OA looks at the entire plan, not just the next tool to call. Optimizes for business outcomes: fastest overall with highest quality under budget, never violate policy, handle errors automatically.
Routes steps between cloud and edge devices live per request using NeuroSplit. Multi-model and multi-tool, each step uses the best possible model, API, or data source selected based on your constraints.
See exactly how agents plan and execute tasks. Complete visibility into model choices, execution steps, and decision paths for debugging and optimization.
Built for developers who need both automation and control. Set constraints, observe decisions, and iterate on agent behavior without complex configuration.
Drop OA into a single component of your system and it plays nicely with the rest. Progressive adoption: start getting value in hours without refactoring your entire codebase.
Skymel OA transforms how developers build AI applications, from static chains to dynamic, self-managing agents.
from skymel import OrchestratorAgent
# Agent created from natural language description
agent = OrchestratorAgent(
prompt="Customer support agent that can research issues,
provide solutions, and escalate when needed",
policies={
"budget": 5.00,
"privacy": "customer_data_local"
}
)# Agent handles the request automatically
response = await agent.run(
"Customer says premium subscription isn't working"
)
# See what the agent did
print(response.solution)
print(response.next_steps)Creates specialized agent from your prompt with the right capabilities, tools, and constraints
Agent analyzes the request and creates an optimal execution plan with multiple steps and decision points
Autopilot executes the plan, adapting in real-time based on results, errors, and changing requirements
Continuously optimizes performance, cost, and quality while maintaining full observability and compliance
Enterprise-grade security designed for production workloads with data privacy controls
Built to handle growing workloads with cloud and edge orchestration capabilities
Complete visibility into agent decisions and workflow execution for debugging and optimization
Designed for production reliability with error handling and fallback mechanisms
Start with one workflow. Scale gradually as you see value. Designed to work alongside your existing systems.
Begin with a single use case and expand gradually across your organization
Complete visibility into agent decisions and workflows for operational oversight
Automatic model selection and optimization helps control AI infrastructure spending
Be among the first to build with Skymel OA
Experience Skymel OA capabilities through ARIA
Available NowWork directly with our team to shape the platform
Accepting ApplicationsFull access to Skymel OA APIs and development tools
6 WeeksJoin developers building intelligent, adaptive AI workflows with Skymel OA