👑 SUPEROPTIX AI
Full Stack Agentic AI Framework
Powered by DSPy. Refined by Superagentic AI.
🔍 What is SuperOptiX?
SuperOptiX is a Full-Stack Agentic AI Framework designed to help developers and teams build optimized, production-grade AI agents from day one. It brings together declarative agent specification, automatic optimization, built-in evaluation, and multi-agent orchestration—all grounded in the principles of test-driven development and context engineering.
Unlike most frameworks that bolt on evals and monitoring as an afterthought, SuperOptiX makes evaluation, optimization, and guardrails core to the development lifecycle. Whether you're deploying a single agent or a coordinated system of agents, SuperOptiX gives you the power to go from prototype to production—faster, safer, and smarter.
🎯 Declarative by Design. ⚡ Optimized by Default. 🎼 Orchestration-Ready.
With its native DSL (SuperSpec), DSPy-based optimization layer, structured agent tiers (Oracles, Genies, Protocols, Superagents, Sovereigns), and full-stack abstractions, SuperOptiX empowers you to build reliable, adaptive, and intelligent agentic systems—without reinventing the wheel.
⚡ Core Features
🎯 Evaluation-First by Design
Agents are defined and validated using BDD-style specs before orchestration. Every agent starts with behavior-driven goals.
✅ BDD-Style Spec Runner
Write agent specs in a human-readable DSL (SuperSpec), execute them as tests, and optimize your agents iteratively—just like TDD for AI.
⚙️ DSPy-Powered Optimization Engine
SuperOptiX builds on DSPy for declarative optimization of agents, prompts, chains, and protocols—with transparent tracing and tuning.
🚀 Agentic DSPy Evolution
Custom modules for multi-agent coordination, protocol support (MCP, A2A), and advanced agentic scenarios beyond standard DSPy.
🧩 Modular Optimization Architecture
DSPy as primary adapter with framework-agnostic design. Ready to integrate future optimization frameworks while maintaining user choice.
✍️ Prompt & Context Optimization
Automatically decompose, optimize, and test prompts and embedded context for better grounding, relevance, and goal alignment.
⚡ Automated Agent Pipeline Generation
Define your high-level spec, and SuperOptiX generates the entire agent optimization pipeline—including DSPy Signatures, Modules, Evaluation, and Optimization—from prompt tuning to memory wiring.
📄 SuperSpec DSL
A domain-specific language to declaratively define agents, roles, evaluation specs, tools, and coordination flows. Think Gherkin for agents.
🧠 Inbuilt Memory System
Modular memory layers (short-term, vector, long-term, ephemeral) that can be composed per agent, protocol, or tier.
📈 Built-in Evals
Native evaluation suite for functional, behavioral, and optimization-level tests. Run metrics, comparisons, and scenario-based scoring.
📦 Context Engineering Layer
Structured context frames, templating, prompt modularization, and evaluation-backed refactoring tools.
🤖 Model & Inference Management
Plug-and-play with OpenAI, Anthropic, HuggingFace, Ollama, Groq, or Apple MLX. Swap models dynamically, locally or via API.
🏪 Marketplace for Prebuilt Agents & Tools
Discover and deploy pre-optimized Genies, Protocols, memory templates, and tooling components. Build faster with reusable agents.
📊 AgentOps Layer
Observability, replay, versioning, and adaptive agent debugging. Perfect for production feedback and runtime evaluation.
🧠 SuperOptiX & DSPy
Agentic DSPy - Taking Optimization to the Next Level
SuperOptiX harnesses the full power of DSPy's optimization principles and elevates them to the agentic layer.
We're not just a DSPy wrapper—we're Agentic DSPy.
DSPy is the most powerful optimization framework in the AI space and the only framework that systematically optimizes language model programs. SuperOptiX recognizes this strength and builds upon DSPy's revolutionary optimization-first approach, extending it specifically for agentic AI and multi-agent orchestration.
🎯 Why DSPy is Perfect for Agentic Systems
DSPy's iterative optimization principles align perfectly with Test-Driven Development (TDD) and Behavior-Driven Development (BDD) methodologies. It's as if DSPy was designed specifically for building reliable, testable agentic systems:
| DSPy Core Strength | Agentic System Need | SuperOptiX Innovation |
|---|---|---|
| Optimization-First | Reliable agent behavior | BDD-style agent specifications |
| Assertions & Evaluations | Agent validation | Multi-tier evaluation framework |
| Signature Generation | Context engineering | Advanced prompt optimization |
| Module Composition | Multi-agent coordination | Orchestra-level optimization |
🚀 SuperOptiX: The Agentic Evolution of DSPy
Advanced Custom Modules for Agentic AI
SuperOptiX includes sophisticated modules designed specifically for agentic and multi-agent scenarios that extend beyond the standard DSPy offering:
Multi-Agent Coordination Modules
Advanced orchestration patterns for complex multi-agent scenarios
Protocol Support Modules
MCP (Model Context Protocol) and A2A (Agent-to-Agent) integration
Memory-Optimized Modules
Context-aware memory management across agent interactions
Guardrail Modules
Safety and compliance checks for production deployment
⚡ Automatic Pipeline Generation from Specifications
SuperOptiX uses DSPy's optimization engine to automatically generate entire agent pipelines from high-level specifications:
🧩 Modular Optimization Architecture
SuperOptiX takes a modular approach to optimization and evaluation:
💫 The Perfect Marriage: DSPy + Agentic AI
DSPy's emphasis on systematic optimization, evaluation-driven development, and composable modules makes it the ideal foundation for building robust agentic systems. SuperOptiX extends this foundation with:
Application-Layer Abstractions
SuperSpec DSL for declarative agent building
BDD Testing Framework
Behavior-driven specifications for agent validation
Multi-Tier Architecture
Progressive complexity from Oracles to Sovereigns
Production-Ready Features
Memory management, observability, and deployment tools
SuperOptiX transforms DSPy from a research framework into a production-ready agentic AI platform.
💎 SuperSpec - The Heart of Agent Building
SuperSpec is our declarative DSL that makes agent building as simple as writing a specification.
Think of it as "Kubernetes for AI agents" - you describe what you want, and SuperOptiX builds the entire pipeline.
🤔 Why SuperOptiX?
🚨 The Challenge
Building production-grade AI agents remains a significant challenge. Most available frameworks are designed for demos, not deployment, and rely on hardcoded prompts with no built-in optimization. This leads to fragile systems and reinvention of common components.
As a result, over 95% of AI projects never make it to production—not due to lack of ambition, but due to lack of the right tooling, standards, and engineering discipline.
- ❌ Fragile, hardcoded prompts
- ❌ No systematic optimization
- ❌ Lack of evaluation frameworks
- ❌ Production deployment challenges
✨ Our Solution
SuperOptiX AI is the first evolution‑first, behavior‑driven framework that combines:
- ✅ Built‑in Evaluation (BDD first): Write behavior‑driven specs that serve as executable tests.
- ✅ Optimization at the Core: Data‑driven performance tuning, powered by DSPy.
- ✅ Orchestration‑Ready Pipelines: Kubernetes‑style DSL and multi‑agent coordination.
- ✅ Production‑Grade Monitoring: Guardrails, observability, and safe‑by‑design architecture.
All within a single, end‑to‑end solution—no stitching together siloed tools.
🆓 Start Free Today!
Oracle & Genie tiers are completely FREE to try! No credit card required.
- 🧙♂️ Oracle Tier: Simple Q&A and automation - FREE
- 🧞♂️ Genie Tier: Multi-step reasoning with tools & RAG - FREE
- 🎭 Protocol Tier+: Advanced enterprise features - Commercial
🎉 New to SuperOptiX?
Start with our Quick Start Guide - designed to be your "wow moment" with SuperOptiX!
Need to set up first? Check out Installation and LLM Setup to get everything configured.
Or jump directly to Create First Genies Agent to get hands-on experience.
🌟 What Makes SuperOptiX Special?
SuperOptiX isn't just another agent framework — it's the world's first optimization-first, orchestration-ready, evaluation-built Agentic AI framework. Here's what sets us apart:
⚡ Optimization-First Philosophy
Traditional AI frameworks treat optimization as an afterthought. SuperOptiX puts it at the core:
| Traditional Approach | SuperOptiX Approach |
|---|---|
| ❌ Build → Hope it works | ✅ Specify → Evaluate → Optimize → Deploy |
| ❌ Manual prompt tuning | ✅ Automated DSPy optimization |
| ❌ No systematic testing | ✅ BDD-driven evaluation |
| ❌ Production surprises | ✅ Safe-by-design validation |
🏆 The SuperOptiX Differentiator
| Feature | SuperOptiX | Other Frameworks |
|---|---|---|
| Agent Optimization | ✅ Built-in DSPy optimization | ❌ (DSPy exception) |
| Agent Creation & Orchestration | ✅ Complete framework | ✅ (basic) |
| InBuilt Model Management | ✅ MLX/HF/Ollama/LM Studio | ❌ |
| BDD/TDD Spec Runner | ✅ Professional evaluation | ❌ |
| Local Inference + Memory + RAG | ✅ Integrated solution | ✅ (external) |
| DSL for Agent Specs (SuperSpec) | ✅ Kubernetes-style | ❌ |
| Tracing & Observability | ✅ Built-in monitoring | ✅ |
🏗️ Progressive Tier System
!!! info "💼 Commercial Package with Free Tiers" SuperOptiX is a commercial package, but we offer Oracle and Genie tiers completely free to try! This allows you to experience the power of SuperOptiX before considering our commercial tiers (Protocol, Superagent, and Sovereign) for advanced enterprise features.
Scale from simple to enterprise complexity with our 5-tier architecture inspired by Nick Bostrom's Superintelligence and Sam Altman's AGI stages:
Simple, fast question answering system that involves interaction with LLMs and responding to your queries. There is no connection to external data and quality of output directly depends on the quality of the LLMs used.
- Status: ✅ Available (Free to Try)
- What: Simple, single-purpose agents
- Use Case: Basic automation, simple Q&A
- Example: FAQ bot, data formatter
- Complexity: Low
- Cost: 🆓 Free
Key Features: - Single-step reasoning - Template-based responses - Built-in optimization and validations
Includes: - Any LLM Support, Model Management, Few Shot Optimization, Simple Evals, BDD Spec Runner, Simple Sequential Multi Agent Orchestra, Static Pipelines Code with SuperOptiX DSPy Mixin, Demo Purpose Outputs, Basic tracing and observability
Multi-step reasoning agents that involve interaction with LLMs and external systems like knowledge and tools. This system uses reasoning and action (ReAct) to perform controlled actions on your behalf.
- Status: ✅ Available (Free to Try)
- What: Multi-step reasoning agents
- Use Case: Customer service, content creation
- Example: Support agent, content writer
- Complexity: Medium
- Cost: 🆓 Free
Key Features: - Multi-step reasoning with ReAct - Dynamic tool selection and usage - Memory integration and learning through RAG
Includes: - Function calling LLM Support, Custom Function calling DSPy tools, RAG with favorite vectorDB Support, Model Management with MLX, HF, Ollama and LM Studio, Few Shot and Labeled Few Shot Optimization, Simple Evals, Basic DSPy Memory Support, BDD Spec Runner basic metrics, Sequential Multi Agent Orchestra, Static Pipelines Code with SuperOptiX DSPy Mixin, Demo Purpose Outputs with usage tracking, Basic Tool Tracing Observability and Tool call, Multi-Agent Orchestra with demo outputs
Highly advanced tier with support of industry-evolving protocols like MCP and A2A, covering all features from Oracles and Genies. This layer uses advanced industry protocols to make agents better and communicate with LLMs and each other.
- Status: 🔒 Commercial (Contact Us)
- What: Complex workflow agents
- Use Case: Business processes, decision making
- Example: Sales qualification, risk assessment
- Complexity: High
- Cost: 💼 Commercial
Key Features: - Advanced agents with MCP & A2A protocols - Integrate with external APIs, systems, workflows
Includes: - Everything from Oracles and Genies, Custom Function calling DSPy tools, Agentic RAG with popular vectorDB Support, AgentVectorDB Integration, Advanced Model Management with vLLM, SGLang, TGI servers for Production deployment, Advanced DSPy and Custom Optimizers, Layered Memory Support, Automated Basic Synthetic Data Generation, BDD Spec Runner with advanced metrics and validations, Parallel Multi Agent Orchestra, Controlled DSPy Pipelines (No Mixin), Production Worthy Agent Output format suitable for multi-agent system, Advanced Tracing Observability and Tool, Integration with third party tools like MLflow, Basic Planner → Executor Multi Agent Orchestra, Basic Kubernetes Style Orchestra
Multi-agent systems with coordination where a lead agent called Superagent may spawn automated subagents to perform tasks and work with other superagents. This involves higher levels of orchestration managed by AgentLines.
- Status: 🔒 Commercial (Work in Progress)
- What: Multi-agent systems with coordination
- Use Case: Complex business workflows
- Example: E-commerce platform, research team
- Complexity: Expert
- Cost: 💼 Commercial
Key Features: - Superagents orchestrating other agents - AgentLines for scalable multi-agent governance
Tentative Features: - Everything from Oracles, Genies and Protocols, Agentic DSPy Pipeline for Superagent, Advanced Model Management with vLLM, SGLang, TGI servers for Production deployment, Integration with high level GPU infra and MLOps tools for deployment, Combination of LLM and Fine Tuned SLMs, Context Management with VectorDBs and Advanced Memory, Agentic BDD Spec Runner within orchestra and AgentLines, Human in the loop interaction based on defined criteria, Integration with third party DevOps, MLOps Cloud providers
Autonomous AI systems suitable for large-scale AI operations and enterprise workflows. These are the highest level of AI autonomy with advanced multi-agent orchestration and strategic planning.
- Status: 🔒 Commercial (Coming Soon)
- What: Autonomous AI
- Use Case: Large-scale AI operations
- Example: AI-powered company, research lab
- Complexity: Enterprise
- Cost: 💼 Commercial
Key Features: - Advanced multi-agent orchestration - Strategic planning and execution
Tentative Features: - Automatic discovery of agents based on task or goal, Ephemeral Agents making decisions and handling tasks, Integration with agent marketplace for choosing agents for tasks, Multiple LLM and Fine Tuned SLMs, Context Management with VectorDBs and Advanced Memory, Agentic BDD Spec Runner within orchestra and AgentLines, Integration with Multiple third party DevOps, MLOps Cloud providers
🔧 Key Capabilities
🚀 Ready to Build the Future of AI?
Join the SuperOptiX movement to create intelligent, optimized, and reliable AI agents.
🆓 Start FREE today with Oracle & Genie tiers - no credit card required!
👑 SuperOptiX: The King of Agent Frameworks - Where optimization meets intelligence.