Research Foundation

Our research agenda is driven by a practical goal: making AI assistants more affordable, more reliable, and genuinely useful across industries. We pursue three interconnected research directions that together form a comprehensive approach to building production-grade AI systems.

AI Agent Architecture

We research agent architectures designed to make AI copilots and generative assistants both more cost-effective and more reliable. Our core concept is the agent as a recursive orchestrator of skills: the orchestration itself can be guided by prompts or code, while skills are simply prompts or tools the assistant can invoke. This modular, composable approach enables sophisticated behaviors while keeping systems maintainable and predictable.

Specification-Driven R&D

We believe rigorous specification management is the key to unlocking AI's creative potential. Our research transforms AI into a true compiler from specifications to artifacts: code, diagrams, research theories, articles, novels, images, films, and any other creative output. By keeping specifications clear, traceable, and versioned, we enable reproducible, auditable AI-assisted creation across every domain, from software engineering to scientific research to artistic production.

Trustworthy AI Research

We investigate neurosymbolic solutions to address the fundamental challenges of trustworthy AI: the opacity of results, bias in training data, and the hallucinations that prevent adoption in highly regulated industries. Built around AGISystem2, our research has produced tangible results: working systems for knowledge representation and formal, verifiable reasoning that can explain their conclusions and guarantee logical consistency.