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Reific

Reific is a YC Fall 2026 (F26) company. Based in San Francisco, CA, USA. Team of 1.

  • Generative AI
  • Machine Learning
  • Reinforcement Learning
  • Infrastructure
  • AI

About Reific

GPAgent's own fund-neutral profile, written from public information. Updated Nov 6, 2026.

Summary

Reific builds reinforcement learning environments that train AI agents to reason over time-series data, sold to frontier AI labs. Each environment uses real, de-identified records from health devices, industrial equipment, and scientific and compute infrastructure, and streams data on a live clock so that an agent's answer is graded against what actually happened. The product replaces static, frozen benchmarks that cannot test whether a model can watch a moving system for days or weeks and act at the right moment.

Business model

Omit: pricing structure not shown in sources.

Go-to-market

Frontier AI labs are the buyers. Labs request sample environments directly through the website, making initial access self-serve, and Reific also offers direct researcher conversations for deeper engagement.

From the Y Combinator listing

How Reific describes itself in Y Combinator's public directory.

RL environments for superhuman reasoning over time

Reific builds RL environments for superhuman reasoning over time, for the frontier labs that train agents. AI has learned to reason over text and code. But most of what matters in the real world shows up as numbers that change every second: a heartbeat, a gearbox, a GPU cluster. No human can track thousands of signals at once, but AI should be able to. In our environments, data streams in on a clock while the agent works, and every action is graded by what actually happened. Most AI training today teaches models to match human experts. We treat human performance as the floor. Each environment comes from real, de-identified records, in three task families: personal agents, industry, and science & compute. Today, even the best frontier model averages under 50% on each family. Training an open model on our environments raised its full-solve rate on unseen tasks by 54% (from 25.6% to 39.5%), with no loss on general benchmarks. Our mission is to build the infrastructure that keeps AI climbing the frontier, long past human level in the real world.

Facts

Industry
B2B / B2B -> Infrastructure
Location
San Francisco, CA, USA
Team size
1
Status
Active
Stage
Early

Founders (1)

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