Monte Specialized Agents Trained on Your Work
The post-training and continual learning layer for proprietary intelligence. Research-first, embedded with your team.
About
Monte helps companies turn general models into specialized agents that continuously learn from organizational knowledge.
Today's AI applications are general and static. While foundation models become increasingly capable, they fail to specialize to your work and don't learn from how you use them — so every interaction starts from zero. Meanwhile, as token costs climb, companies pay more each day for generic intelligence not built for them.
The future of software is specific and adaptive. The best systems will not just execute work — they will learn from it, measure themselves against real workflows, and improve from experience.
Monte works directly with customers to build the evaluation, memory, and post-training layer that turns organizational knowledge into proprietary intelligence you own.
Build intelligence
that compounds.
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Capture
Extract signal from real work.
Traces, outcomes, policies, and expert judgment become training signal for continual learning.
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Measure
Evaluate against reality.
Build measurements around the workflows, constraints, edge cases, and standards the system has to meet in production.
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Train
Tailor intelligence to the work.
Use reinforcement learning to shape agents around the company's tools, processes, and goals.
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Compound
Keep learning after launch.
Build memory and route outcomes, feedback, and production data back into training, so models keep improving through experience.
Our Team
Monte is built by three Harvard graduates in computer science, statistics, and physics, with backgrounds in AI/RL research at Harvard, MIT Lincoln Lab, and NASA JPL. We've shipped agents, trained models, and built the infrastructure behind systems that learn continuously in production. We're backed by Y Combinator.