Research & Innovation

Engineering trustworthy AI systems that scale human potential through autonomous agents, decentralized networks, and AI-native transformation solutions.

Autonomous Agent Networks

Developing frameworks for collaborative AI systems that can self-organize, negotiate, and solve complex problems autonomously.

  • Multi-agent coordination protocols
  • Emergent behavior analysis
  • Collective intelligence optimization

Brand Presence Optimization for AI

Advanced monitoring and management of brand representation across AI-generated content.

  • AI content monitoring and analysis
  • Brand consistency enforcement
  • Automated correction frameworks

Active Projects

Agent Collaboration Framework

Standards development for AI agent interaction in financial services, model-specific task orchestration, and purpose-built agents for data and API migration tasks.

AI-Powered Financial System Integration

Advanced generative AI tools for blockchain-based financial system integration.

Payment Infrastructure

Stablecoin & tokenized deposit, On-ramp/off-ramp architecture, multi-rail payment gateways, and real-time settlement systems for digital assets.

AI-Native Migration Platform

Revolutionary cost-efficient migration services that transform legacy applications and infrastructure with zero downtime. Our AI-powered approach reduces migration costs by up to 70%.

Long-Term Research Initiatives

Beyond our active projects, we're exploring fundamental questions at the frontier of AI research.

Reward Hacking & Cognitive Spam

Investigating how AI systems can be manipulated to produce unintended outcomes through optimization for specific metrics, and developing frameworks to detect and prevent exploitation through cognitive spam techniques in large language models.

AI Dataset Bias & Stereotyping Detection

Creating comprehensive methodologies and tools to identify, measure, and mitigate biases and stereotypes in AI training datasets, enabling more equitable and representative AI systems.

Cognitive Architecture of Taste

Developing a novel framework for understanding how aesthetic preferences and taste judgments form in human cognition, with applications in personalization algorithms and content recommendation systems.