logo
  • 환경
  • 엔터프라이즈
  • 요금제

Continuous Evals to Train Agents for
Your Workflows

We build reproducible environments, benchmark suites, and training loops so Eigent improves reliably on your enterprise-grade systems in browser and terminal scenarios.

Step 1

Environment Design

Environment Design
Step 2

RL Training Loop

RL Training Loop
Step 3

Agent Performance

Agent Performance

Why Environments Matter for Agents

Agentic enterprise automation is shifting from pure text training to real interactions with business systems. To improve reliability, you need reproducible environments to train and validate agent behavior, plus an end-to-end evaluation loop for continuous measurement and iteration. These environments also enable scenario-specific model training—so you can deploy agents (and models) optimized for your enterprise workflows.

What We Deliver

Enterprise-grade environments, evaluations, training loops built for real systems.

Real-world Benchmarks Built from Enterprise Scenarios
A Reproducible RL environment for Ongoing Training
Training Loop for improving Model Performance in Real-World Environments
Better-performing, more Adaptive Eigent Performance in Your Scenario

Use Cases

Checkout our use cases for our clients.

CRM / ERPBrowser Automation

RL Environment for Browser Automation (CRM / ERP / E-commerce)

We built a suite of reproducible browser-based RL environments for ERP/CRM and e-commerce back-office workflows, paired with 2,000+ real-world task samples for training and evaluating automated task execution models across multi-page enterprise systems.

  • Environments: ERP / CRM / e-commerce management platforms
  • Tasks: single-step search, multi-step chained search, cross-table lookup, data analysis, edit and creation operations (leads/orders/invoices)
RL Environment for Browser Automation
Terminal Environment for Terminal Agents
Linux / UbuntuTerminal Agents

Terminal Environment for Terminal Use

We built a dataset designed to improve terminal agent capabilities, specifically for training and evaluating models on task execution in real Linux/Ubuntu environments. Each entry corresponds to a reproducible containerized environment and a complete terminal task package.

  • Environments: Linux/Ubuntu terminal environments
  • Tasks: tool usage, multi-step operations, and error handling

Trusted by Selected Enterprise Teams

Reference deployments available upon request.
FinanceE-commerceLogisticsIT OperationsCustomer SupportR&D

Build environments that make your agents reliable

Title*
Full Name*
Job Title*
Business Email*
Company Name*
Country/Region*
What types of data or environments are you interested in? * (Select all that apply)
Additional Details about Your Request

Open Source Cowork 데스크톱

100% 오픈 소스 - 직접 호스팅 가능, 무료, 자체 API 키 또는 로컬 모델 사용.

영업팀 문의
Eigent

AI 워크포스 자동화에 대한 최신 소식, 튜토리얼, 출시 정보를 받아보세요.

제품Eigent환경요금엔터프라이즈
둘러보기솔루션활용 사례스킬플러그인블로그
개발자문서GitHubCAMEL-AI오픈소스 펀드파트너
다운로드오픈 소스용
회사회사 소개브랜드채용이용약관개인정보처리방침보안 및 신뢰쿠키 정책환불 및 체험 정책

모든 권리 보유 © 2026 EIGENT UK LTD

Eigent 1.0 새 버전 출시!download