OpenSSA: Small Specialist Agents
Create Domain-Specific
AI Agents
Tackling multi-step complex problems beyond traditional language models
OpenSSA: Small Specialist Agents
Tackling multi-step complex problems beyond traditional language models
Create lightweight, resource-efficient AI agents through model compression techniques
Enhance agent performance with domain-specific facts, rules, heuristics, and fine-tuning for deterministic, accurate results
Enable goal-oriented, multi-step problem-solving for complex tasks via systematic HTP planning and OODAR reasoning
Works seamlessly with popular AI frameworks and tools for easy adoption
Easily integrate new models and domains to expand capabilities
Build AI agents for industrial field service, customer support, recommendations, research, and more
SSMs comprise three key components: a front-end Small Language Model (SLM),
an adapter layer in the middle, and a wide range of back-end domain-knowledge sources.
SLM is a small, efficient, domain-specific model. It forms the frontend of an SSM. It can be compacted from a larger model.
Adapters (eg. LlamaIndex) provide the interface between the SLM and the domain-knowledge backends.
Support for a wide range of text files, documents, PDFs, databases, code, knowledge graphs, models, other SSMs, etc.
SSMs communicate in both unstructured (natural language) and structured APIs, catering to a variety of real-world industrial systems. The composable nature of SSMs allows for easy combination of domain-knowledge sources from multiple models.
OpenSSA significantly boosts the accuracy of Retrieval-Augmented Generation (RAG) systems. It fine-tunes the embedding or completion model with domain-specific knowledge.
Build AI assistants that provide accurate, context-aware responses in customer support, healthcare, and other domains. OpenSSA's domain-specific fine-tuning capabilities enable you to create AI agents that understand and respond to user queries with unprecedented accuracy and relevance.
OpenSSA enables you to create AI agents that can effectively plan and reason within specific domains to solve complex problems.
Create AI agents that can guide field service technicians through complex maintenance and repair procedures.
Build AI assistants that provide accurate, context-aware responses in customer support, healthcare, and other domains.
Create AI agents that can effectively plan and reason within specific domains to solve complex problems.
OpenSSA significantly boosts the accuracy of (RAG) systems, it fine-tunes the embedding or completion model with domain-specific knowledge.
Create AI agents that can guide field service technicians through complex maintenance and repair procedures.
