Self-Evolving Agents
How agents can learn through human interaction, carrying useful feedback into better memory, decisions and workflows.
Explore this areaMOMENTS RESEARCH
We study self-evolving agents shaped by human–AI interaction: how they understand context, plan useful action and improve through feedback. CramAI brings these questions into career growth.
RESEARCH AGENDA
Each area addresses a different part of the same question: how can intelligence keep learning while remaining useful, measurable and governable?
How agents can learn through human interaction, carrying useful feedback into better memory, decisions and workflows.
Explore this areaInternal models that represent state, predict outcomes, simulate alternatives and support closed-loop action.
Explore this areaUnified understanding across language, vision, audio, video, behavior and real-world context.
Explore this areaContinuous measurement of what a person or agent can do, where it fails, how certain it is, and whether it is improving safely.
Explore this areaA long-term research direction, grounded in evaluation, controlled experiments and human oversight.
RESEARCH INTO PRODUCT
CramAI is a career coach agent designed to help you find direction, build relevant skills and take your next step as work changes. Its Learn, Practice, Assess and Improve loop gives our research a practical question: what helps a person make progress toward a career goal?
Explore CramAIMOMENTS RESEARCH · PUBLIC OUTPUTS
Papers, technical reports and public code connect research questions with methods and applications.
Published papers, preprints and accepted research.
No company papers are currently listed.
Methods, observations, evaluation conditions and limitations.
No public technical reports or research notes are currently listed.
Public projects with documentation, versions and license information.
No public code projects are currently listed.
OPEN PROBLEMS
These questions frame research directions. They are not claims of solved capability.
Self-Evolving Agents
Agentic World Models
Omnimodal Intelligence
AI Assessment
COLLABORATION & INTEGRITY
We are interested in joint research, benchmarks and applied pilots with teams that share our commitment to measurable progress, honest limitations and human agency.