OpenSSA: Neurosymbolic Agentic AI for Industrial Problem-Solving

OpenSSA is an open-source neurosymbolic agentic AI framework designed to solve complex, high-stakes problems in industries like semiconductor, energy and finance, where consistency, accuracy and deterministic outcomes are paramount.

At the core of OpenSSA is the Domain-Aware Neurosymbolic Agent (DANA) architecture, advancing generative AI from basic pattern matching and information retrieval to industrial-grade problem solving. By integrating domain-specific knowledge with neural and symbolic planning and reasoning, such as Hierarchical Task Planning (HTP) for structuring programs and Observe-Orient-Decide-Act Reasoning (OODAR) for executing such programs, OpenSSA DANA agents consistently deliver accurate solutions, often using much smaller models.

Key Benefits of OpenSSA

• Consistent and Accurate Results for complex industrial problems
• Scalable Expertise through AI agents incorporating deep domain knowledge from human experts
• Economical and Efficient Computation thanks to usage of small models
• Full Ownership of intellectual property when used with open-source models such as Llama

Getting Started

• Install with pip install openssa (Python 3.12 and 3.13)

• For bleeding-edge capabilities: pip install https://github.com/aitomatic/openssa/archive/main.zip

• Explore the examples/ directory and developer guides and tutorials on our documentation site

API Documentation

Contributing

We welcome contributions from the community!

• Join discussions on our Community Forum
• Submit pull requests for bug fixes, enhancements and new features

For detailed guidelines, refer to our Contribution Guide.