From structured orchestration to verified generation. We're solving the reliability problem that stands between AI and enterprise-grade software.
LLMs lose coherence as complexity rises. We're building the orchestration frameworks and verification systems that restore reliability at scale.
Investigating novel neural architectures beyond the transformer paradigm. State-space models, graph neural networks, and hybrid approaches.
Multi-agent orchestration with test-driven development. Specialized agents that collaborate through structured artifacts and iterative verification.
Advanced retrieval-augmented generation, vector architectures, and semantic memory systems for grounded intelligence.
Exploring reward modeling, RLHF alternatives, and self-improving systems that learn from interaction and feedback.
Where research meets production. We're transforming our findings into tools that developers will actually use.
AI-native tools for the agentic era. Code analysis, visual documentation, and intelligent automation.
Reproducible experimentation for multi-agent systems. Benchmarks, evaluation harnesses, and orchestration.
Our commitment to open source spans decades. From pioneering Java frameworks to modern AI-driven development tools.
Multi-Factor Code Quality Index. Evidence-based static analysis that synthesizes complexity, security, and quality metrics into one actionable score.
PythonState machines in Rust, data science environments, Spring extensions, and more. Decades of open source contributions.
Multi-languageInterested in what we're building? We're selectively exploring partnerships and conversations with aligned teams.
info@integrallis.com