EnterpriseGym Corecraft: Training Generalizable Agents on High-Fidelity RL Environments
#Reinforcement Learning#Corecraft#EnterpriseGym#Surge AI#Agentic RL#High‑fidelity Simulation#Customer Support AI#Enterprise Workflow#Generalizable AI Agents#Open‑Source AI Environments
📌 Key Takeaways
Surge AI introduced <corecraft>, a high‑fidelity RL environment for enterprise simulations
The environment models a customer‑support organization with 2,500+ entities, 14 entity types, and 23 tools
It is the first offering in Surge AI’s <textsc{EnterpriseGym}> suite of agentic RL environments
The purpose is to show that agents trained on such complex settings can generalise beyond their training distribution
Surge AI plans to expand <textsc{EnterpriseGym}> with additional domains to advance adaptive enterprise‑AI systems
📖 Full Retelling
The latest contribution to the AI research community comes from Surge AI, which today announced <corecraft>, a cutting‑edge reinforcement learning (RL) environment that sits at the heart of its newly launched <textsc{EnterpriseGym}> suite. It was posted to arXiv on 2026‑02, marking the first public disclosure of a 2,500‑entity, 23‑tool simulation of a real‑world customer‑support organization. The purpose of the release is to demonstrate that training agents in such a high‑fidelity setting can produce generalisable skills that extend beyond the narrow circumstances on which the agents were originally trained.
<corecraft> models the operational workflow of a midsize tech firm, featuring 14 distinct entity types—including agents, customers, support tickets, and knowledge‑base items—across more than 2,500 individual components. By exposing a single RL agent to this intricate web of interactions, Surge AI hopes to push beyond the typical tab‑limited environments that dominate the literature. The goal is to show that an agent can learn to navigate and optimise in a dense, continually evolving virtual enterprise, and that its knowledge can translate to other agencies with similar relational structures.
In the accompanying announcement, Surge AI stated that <corecraft> is now publicly available for researchers and developers who wish to experiment with agentic behaviours in organisational settings. The company highlights that the environment is designed to be fully operational, allowing agents to orchestrate complex sequences of tool‑based actions, akin to human support specialists interacting with CRM systems, email, and knowledge‑base portals.
Looking ahead, Surge AI plans to evolve the <textsc{EnterpriseGym}> series to include additional domains—such as logistics, finance, and supply‑chain management—each built with comparable fidelity. The broader vision is to accelerate progress on AI systems that can adapt, generalise, and ultimately embed themselves into enterprise workflows without the need for exhaustive retraining on every new domain.
🏷️ Themes
AI Generalization, High‑Fidelity Simulation, Enterprise‑AI Integration, Reinforcement Learning, Agentic Environments
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Deep Analysis
Why It Matters
Training agents in high fidelity enterprise simulations enables them to learn skills that transfer to real world tasks, reducing the gap between simulation and deployment and accelerating AI adoption in business operations
Context & Background
Corecraft is the first environment in Surge AI's EnterpriseGym suite
It models a customer support organization with over 2500 entities, 14 entity types and 23 tools
Agents trained here show improved generalization beyond the training distribution
What Happens Next
Surge AI plans to expand EnterpriseGym with additional complex business scenarios, integrate the platform with popular RL libraries, and encourage academic research on generalization in RL
Frequently Asked Questions
What is EnterpriseGym?
EnterpriseGym is a collection of high fidelity reinforcement learning environments designed to simulate real business operations for training AI agents
How many entities does Corecraft contain?
Corecraft contains over 2500 entities across 14 different types
Will Corecraft be available to the public?
The current release is a research preview; Surge AI will evaluate public access in future updates
Original Source
arXiv:2602.16179v1 Announce Type: new
Abstract: We show that training AI agents on high-fidelity reinforcement learning environments produces capabilities that generalize beyond the training distribution. We introduce \corecraft{}, the first environment in \textsc{EnterpriseGym}, Surge AI's suite of agentic RL environments. \corecraft{} is a fully operational enterprise simulation of a customer support organization, comprising over 2,500 entities across 14 entity types with 23 unique tools, des
