SUPEROPTIXFull-Stack Agentic AIOptimization PlatformBuild once with SuperSpec and compile to your preferred framework.
Powered by DSPy. Refined by Superagentic AI.
You Do Context Engineering.
SuperOptiX Does Agent Engineering.
Once declared, automatic pipelines. Write once, compile everywhere, optimize every layer.
Write your agent as a SuperSpec YAML specification. Define behavior, tools, and goals once.
Generate native pipelines for DSPy, OpenAI, Claude SDK, CrewAI, Google ADK, Pydantic AI, DeepAgents, or Microsoft.
GEPA optimizes across Prompts, RAG, Memory, and Context. Enable with --optimize when ready.
Experimental RLM support with stronger Signature + Module automation. Future-proof your agents.
SuperOptiX is now publicly available for the community to use, inspect, and extend. Here's what ships with the open source release.
SuperOptiX is now publicly available on GitHub. Use it, inspect the code, contribute, and build on top of it.
View on GitHubGenerated pipelines across all supported frameworks are now significantly simpler. The default output is readable and runnable, without heavy runtime scaffolding.
Optimization and evaluation logic now lives behind --optimize, so base pipelines stay focused and clean.
Native generation flows across DSPy, Pydantic AI, Google ADK, OpenAI Agents SDK, DeepAgents, CrewAI, Claude Agent SDK, and Microsoft Agent Framework.
Experimental RLM support with stronger Signature + Module automation from SuperSpec and GEPA-first optimization workflow.
Wire SaaS actions into agents using StackOne connectors. Includes examples like Calendly workflows for connector-driven agentic automation.
Everybody is trying to solve it. Nobody has succeeded. Until now.
Without optimization, AI and agents aren't going anywhere.
Not even close to production.
Optimization at each layer is what makes agents production-worthy.
SuperOptiX is fully focused on solving the optimization of agents at each layer, making them truly production-worthy.
Automatic prompt evolution and refinement
Structured context engineering
End-to-end workflow refinement
Hyperparameter and configuration tuning
SuperOptiX gives you a cleaner path from defining intent to shipping optimized agents
Framework glue code everywhere
Provider-specific logic duplicated
Manual prompt tweaking is endless
Heavy runtime scaffolding
Define intent once in SuperSpec YAML
Generate framework-native pipelines
Optimize with GEPA when ready
Keep code ownership and readability
| Area | Other Frameworks | SuperOptiX |
|---|---|---|
| Pipeline Output | Heavy runtime scaffolding | Minimal, framework-native code |
| Framework Lock-in | Rewrite for each framework | One spec, 8 frameworks |
| Optimization | Manual or framework-specific | Explicit --optimize path with GEPA |
| Code Ownership | Framework abstractions hide logic | Readable, native pipelines you own |
SuperOptiX compiles a single SuperSpec YAML into framework-native agent pipelines across 8 frameworks. Stay close to each framework's native programming model.
Complex reasoning & research
Simple & fast agents
Anthropic Claude agents
Multi-agent teams
Gemini-native integration
Type-safe agents with MCP
Complex planning & reasoning
Enterprise Azure (legacy)
The Genetic-Pareto (GEPA) optimizer works across all 8 supported frameworks. Enable optimization only when needed with the explicit --optimize path.
We're continuing to expand SuperOptiX
Improved optimization ergonomics and GEPA-focused workflows
Deeper connector-driven agentic workflows with SaaS integrations
RLM experimentation across more frameworks and use cases
Better debugging UX and observability tooling