Learn by Doing
Tutorials
Hands-on paths through the engine, MCP, and conversational workflows. Rows marked Coming soon point at placeholders—not mature curricula.
Getting Started with Sematryx
Solve your first optimization problem and learn core concepts
Problem Setup: Objectives & Constraints
Define objective functions, bounds, and constraints for complex optimization problems
Engine configuration
Tune agentic routing, explanation depth, and adaptive learning presets for your workloads
Understanding Optimization Results
Interpret results, explanations, convergence metrics, and audit trails
Domain-specific optimization
Illustrative vertical examples; packaged domain libraries remain limited—see Product and Use cases
Extending domain libraries
Roadmap tutorial—extension APIs and catalog are not generally available yet
Advanced Optimization Strategies
Multi-strategy optimization, Private Learning Store, and performance tuning
MCP Agent Demo
See how AI agents use MCP to solve complex optimization problems they would otherwise struggle with
Conversational Optimization
Create optimization problems through natural language conversation with an AI agent
Interactive Jupyter notebooks
Run these notebooks locally or in Google Colab. Perfect for hands-on learning with the Sematryx SDK.
Quick Start
Your first optimization in 5 lines of code. Install, initialize, optimize.
Portfolio Optimization
Financial optimization with constraints, risk parity, and audit trails.
Domain Examples
Healthcare, supply chain, marketing, and ML hyperparameter tuning.
MCP Agent Demo
See how AI agents use MCP to solve complex optimization problems.
Conversational Optimization
Create optimization problems through natural language conversation with an AI agent.