Monte
Specialized Agents Trained on Your Work
Monte is an applied research lab and platform that provides post-training and continual learning infrastructure for AI agents. It addresses the problem that general foundation models remain static and fail to specialize to an organization’s specific work, requiring every interaction to start from zero while token costs continue to rise. Monte helps companies turn general models into specialized agents that continuously learn from organizational knowledge and improve from experience.
The platform captures signal from real work traces, outcomes, and expert judgment, then measures performance against defined workflows and constraints. It supports post-training methods including supervised fine-tuning (SFT), reinforcement learning (RL), and distillation on any open-weight model. Monte offers full training visibility with live metrics and trace recording, serverless or in-cloud deployment options, and a CLI for running evaluations and training. It integrates with coding agents like Claude Code, Codex, or Cursor.
Monte is designed for enterprise teams that need proprietary intelligence built from their own data and workflows. The company works embedded with client teams as a research-first service. Pricing and packaging details such as free plans, trials, or seat-based models are not specified on the website.
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