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Agentic Research

Specializing in:

  • AI Alignment
  • Workforce Augmentation
  • AI Autonomous Company Frameworks

Agentic Research is an independent alignment research group focused on ensuring beneficial AI progression. We stress-test foundation models in complex, long-horizon tasks to identify and mitigate novel failure modes. Our goal is to provide actionable feedback to model developers and publish research that contributes to the safe and robust deployment of advanced AI systems. We operate on a non-competitive, collaborative basis.

Request Research Access

Core Research Vectors

alignment.py

Alignment Research

Developing frameworks for ensuring AI systems behave in accordance with human values and intentions across diverse operational environments as they become more capable. Our work spans value learning, interpretability, and robustness to distributional shift.

  • Value specification techniques
  • Interpretability methods
  • Robustness validation protocols
augmentation.py

Workforce Augmentation

We explore how agentic AI can serve as a cognitive multiplier for the human workforce. This involves creating sophisticated, tool-using agents that can assist with complex professional tasks, from software engineering to scientific research. This applied research provides a real-world testbed for model capabilities, reasoning, and reliability.

  • Human-AI collaboration frameworks
  • Cognitive task optimization
  • Real-time assistance systems
autonomous.py

AI Autonomous Companies (AAC)

As we prepare for Superintelligence, we are developing frameworks for AI-Autonomous Companies. A play on Decentralized Autonomous Organizations (DAOs), AACs are business entities where core operational, strategic, and creative roles are orchestrated by a collaborating cohort of AI agents. This research pushes the boundaries of multi-agent collaboration, economic reasoning, and long-term autonomous operation, providing unique insights into the capabilities and safety requirements of frontier models.

  • Self-governance mechanisms
  • Resource allocation algorithms
  • Market adaptation strategies

Contact Information

contact.txt

Email: [email protected]

Phone: +44 207 123 8544

Address: 71-75 Shelton St, London WC2H 9JQ

Legal Entity: Agentic Ltd (LEI: 13069387)

Early Access Collaboration

orchestrate.sh

We believe that a diversity of research approaches is critical for AI safety. As a small, focused group, we are positioned to explore niche, high-complexity applications that larger organizations may overlook. Granting us early access to preview models allows for:

  • Novel Application Testing: Evaluating model performance on long-horizon, multi-agent tasks that are not part of standard test suites.
  • Alignment Feedback Loop: Identifying and documenting sophisticated failure modes to help improve model safety and alignment.
  • Non-Competitive Research: Our commitment is to publish findings and provide detailed feedback, not to develop competing products or foundational models.

We seek collaborative access to new AI models and tools to further this research. We are prepared to adhere to strict usage policies and provide detailed reports on our findings.

To grant access to preview models:

  • Email [email protected] with your model details
  • Include your organization's legal entity information
  • Describe your research goals and requirements
Get In Touch
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