🏗️ Agent Tiers by Maturity Level

Build a new agent from scratch or optimize the agents you already havewith SuperOptiX mapped to clear maturity tiers.

Start with a greenfield agent or plug in your existing DSPy, Pydantic AI, CrewAI, OpenAI SDK, or custom stack. Each tier represents a layer of sophistication, from simple Oracles to fully autonomous Sovereigns, with custom pricing per maturity layer.

5 Maturity Layers

On-Premise Deployment

You Own Everything

Build New Agents from Scratch

Design completely new agents, aligned to the right maturity tier from Day 1.

Start at Oracles for simple Q&A or jump directly to Genies or Protocols for multi-tool, multi-step workflows.
Use SuperSpec + SuperOptiX to define behavior, tools, memory, and context once, then compile to your preferred framework.
Grow into Superagents and Sovereigns as your use cases and trust levels evolve.

Optimize Existing Agents

Optimize existing agents with SuperOptiX to make them Production-Ready for your environment.

Connect agents built with DSPy, Pydantic AI, CrewAI, OpenAI SDK, Google ADK, Microsoft or custom stacks.
Use GEPA Optimizer and SuperOptiX evaluation to increase accuracy, stability and safety without rewriting your agents.
Map your agent's current capabilities to a maturity tier and optimize layer by layer instead of doing a risky rewrite.
SuperOptiX makes your agents Production-Ready by choosing the right framework, GEPA configuration, observability stack and guardrails for your custom needs.

Forward Deployed Agents (FDA) Model

We Deploy. You Train. They Deliver.

SuperOptiX is deployed directly into your environment as an on-premise sandbox. You train agents with your own data. They deliver results. Once outcomes are proven, we scale together.

We Deploy

SuperOptiX deployed on-premise, private, and secure

You Train

Train agents with your own data, workflows, and constraints

They Deliver

Agents learn, adapt, and evolve continuously

Our Philosophy

You Own Your Data

All data stays on your infrastructure. Zero data leaves your environment.

You Own Your Agents

Agents are trained on your premises. You have full control and ownership.

You Own Your Outcomes

Prove value before commitment. Scale together once outcomes are proven.

🚀 Tier Overview by Maturity Level

Build agents based on their maturity level or layer. Each tier represents a different sophistication level, from simple question-answering to autonomous decision-making. Custom pricing for each layer.

Tier	Maturity Level	Status	Pricing	Complexity	Use Case
🧙‍♂️ Oracles Maturity Level 1 - Entry	Level 1 Low	Available	Custom Pricing Free to explore. Pro tools optional	Low	Basic automation, simple Q&A
🧞‍♂️ Genies Maturity Level 2 - Intermediate	Level 2 Medium	Available	Custom Pricing Based on agent complexity and deployment	Medium	Customer service, content creation
🎭 Protocols Maturity Level 3 - Advanced	Level 3 High	Available	Custom Pricing Based on agent maturity layer and deployment scope	High	Business processes, decision making
🤖 Superagents Maturity Level 4 - Expert	Level 4 Expert	Available	Custom Pricing Tailored enterprise deployment	Expert	Complex business workflows
👑 Sovereigns Maturity Level 5 - Autonomous	Level 5 Autonomous	Available	Custom Pricing Invite-only / Strategic collaboration	Autonomous	Large-scale AI operations

Custom Pricing Based on Agent Maturity Level

Pricing is customized based on the maturity layer you choose, deployment scope, and your specific requirements. All tiers are deployed on-premise, private, and secure through our Forward Deployed Agents (FDA) model. You own your data, agents, and outcomes.

Progressive maturity layers

On-premise deployment

Prove value before scale

🧙‍♂️ Oracles

Maturity Level 1 - Entry

Simple, fast question answering systems with LLM interaction

Maturity Level 1

Available

Custom Pricing

Free to explore. Pro tools optional

Single-step reasoning

Template-based responses

Built-in optimization and validations

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

Examples:

FAQ bots

Data formatters

Simple Q&A systems

Text processors

Basic chatbots

Information retrieval

oracles_agent.yaml

# oracle_agent.yaml
apiVersion: agent/v1
kind: AgentSpec
metadata:
  name: faq-bot
  tier: oracle
 
spec:
  language_model:
    provider: openai
    model: gpt-4o
 
  persona:
    role: "FAQ Assistant"
    description: "Answers common questions"
 
  tasks:
    - name: "answer_question"
      description: "Provide helpful answers"
 
  optimization:
    type: "basic"
    metrics: ["accuracy", "response_time"]
 
  evaluation:
    type: "simple"
    test_cases: 10

🧞‍♂️ Genies

Maturity Level 2 - Intermediate

Multi-step reasoning agents with tools and memory

Maturity Level 2

Available

Custom Pricing

Based on agent complexity and deployment

Multi-step reasoning with ReAct

Dynamic tool selection and usage

Memory integration and learning through RAG

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

Examples:

Customer support agents

Content writers

Research assistants

Data analysts

Code assistants

Documentation generators

genies_agent.yaml

# genie_agent.yaml
apiVersion: agent/v1
kind: AgentSpec
metadata:
  name: support-agent
  tier: genie
 
spec:
  language_model:
    provider: openai
    model: gpt-4o
 
  tools:
    - name: "knowledge_base"
      type: "rag"
      source: "company_docs"
      vector_db: "chromadb"
    - name: "ticket_system"
      type: "api"
      endpoint: "https://api.company.com/tickets"
 
  memory:
    type: "conversation"
    max_tokens: 4000
    vector_store: "redis"
 
  reasoning:
    type: "react"
    max_steps: 5
 
  optimization:
    type: "advanced"
    metrics: ["accuracy", "response_time", "user_satisfaction"]

🎭 Protocols

Maturity Level 3 - Advanced

Advanced agents with industry protocols and complex workflows

Maturity Level 3

Available

Custom Pricing

Based on agent maturity layer and deployment scope

Advanced agents with MCP & A2A protocols

Integrate with external APIs, systems, workflows

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

Examples:

Sales qualification

Risk assessment

Compliance monitoring

Workflow automation

Enterprise integrations

Complex business processes

protocols_agent.yaml

# protocol_agent.yaml
apiVersion: agent/v1
kind: AgentSpec
metadata:
  name: sales-qualifier
  tier: protocol
 
spec:
  protocols:
    - name: "MCP"
      version: "1.0"
    - name: "A2A"
      version: "1.0"
 
  coordination:
    type: "hierarchical"
    leader: "sales-manager"
 
  integrations:
    - name: "crm"
      type: "salesforce"
    - name: "email"
      type: "outlook"
    - name: "calendar"
      type: "google_calendar"
 
  memory:
    type: "layered"
    layers: ["conversation", "knowledge", "long_term"]
 
  optimization:
    type: "custom"
    optimizer: "enterprise_optimizer"
    metrics: ["conversion_rate", "response_time", "accuracy"]

🤖 Superagents

Maturity Level 4 - Expert

Multi-agent systems with coordination where a lead agent called Superagent may spawn automated subagents and work with other superagents.

Maturity Level 4

Available

Custom Pricing

Tailored enterprise deployment

Superagents orchestrating other agents

AgentLines for scalable multi-agent governance

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

Examples:

E-commerce platforms

Research teams

Trading systems

Content studios

Enterprise platforms

AI-powered companies

superagents_agent.yaml

# superagent_orchestra.yaml
apiVersion: agent/v1
kind: OrchestraSpec
metadata:
  name: ecommerce-platform
  tier: superagent
 
spec:
  superagents:
    - name: "product-manager"
      role: "coordinator"
      agents: ["researcher", "writer", "reviewer"]
    - name: "customer-service"
      role: "specialist"
      agents: ["faq-bot", "escalation-handler"]
 
  infrastructure:
    gpu: true
    scaling: "auto"
    monitoring: "comprehensive"
 
  coordination:
    type: "hierarchical"
    communication: "agent_lines"
 
  optimization:
    type: "distributed"
    strategy: "multi_agent_optimization"

👑 Sovereigns

Maturity Level 5 - Autonomous

Autonomous AI systems suitable for large-scale AI operations and enterprise workflows with the highest level of AI autonomy.

Maturity Level 5

Available

Custom Pricing

Invite-only / Strategic collaboration

Advanced multi-agent orchestration

Strategic planning and execution

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

Examples:

AI-powered companies

Research labs

Autonomous systems

Strategic advisors

Self-managing platforms

Autonomous organizations

sovereigns_agent.yaml

# sovereign_system.yaml
apiVersion: agent/v1
kind: SovereignSpec
metadata:
  name: ai-company
  tier: sovereign
 
spec:
  autonomy:
    level: "full"
    decision_making: "strategic"
    self_improvement: true
 
  discovery:
    agent_discovery: true
    task_decomposition: true
    resource_allocation: true
 
  governance:
    type: "constitutional"
    safety_measures: "comprehensive"
    human_oversight: "minimal"
 
  optimization:
    type: "autonomous"
    self_improvement: true
    strategic_planning: true

Ready to Build Agents by Maturity Level?

Through our Forward Deployed Agents (FDA) model, we deploy SuperOptiX directly into your environment as an on-premise sandbox. Choose your agent maturity level and get a custom quote based on your needs.

Deploy Agents, Not Teams

Free to deploy. Free to experiment. Free to learn. Scale together once outcomes are proven.

You Own Your Data

All data stays on your infrastructure

You Own Your Agents

Agents trained on your premises

You Own Your Outcomes

Prove value before commitment