Autonomous Reasoning, Multi-Step Planning & Tool Use

Agentic AI

Building AI agents that can plan, reason, use tools, and execute complex multi-step tasks autonomously.

Overview

Agentic AI represents the next frontier of artificial intelligence — systems that not only understand instructions but autonomously plan and execute multi-step tasks, use external tools, browse the web, write and run code, and iteratively improve their outputs.

Mentneo's agentic research focuses on reliable long-horizon task execution, safe tool use, multi-agent collaboration, and sandboxed code execution environments.

Key Research Topics

  • ReAct-style reasoning
  • Tool use & function calling
  • Multi-agent systems
  • Long-horizon planning
  • Sandboxed code execution
  • Memory & persistence
  • Agent evaluation frameworks
  • Self-correction

Products Using This Research

Mentneo Agents platformEnterprise workflow automationResearch automationSoftware engineering agents

Agentic AI — Common Questions

An AI agent is a system that perceives its environment, makes decisions, and takes actions to achieve goals — often across multiple steps. Unlike a simple chatbot, an AI agent can use tools (web search, code execution, APIs), remember past interactions, and autonomously plan sequences of actions to accomplish complex objectives.

Mentneo agents operate in autonomous loops: they break goals into sub-tasks, select and use appropriate tools, evaluate results, and iterate until the task is complete. They maintain working memory across steps and can coordinate with other specialized agents in multi-agent pipelines.

Yes. All Mentneo agents run in sandboxed environments with configurable permission scopes. We implement human-in-the-loop checkpoints for high-stakes actions, provide full audit logs, and enforce rate limiting. Our AI safety research team reviews all agentic capabilities before production release.

Related Research Areas

Large Language ModelsReasoning ModelsAi SafetyAutonomous Systems