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Documentation Index

Fetch the complete documentation index at: https://docs.eigenai.com/llms.txt

Use this file to discover all available pages before exploring further.

EigenData-CLI generates high-quality datasets for agent evaluation and training. Below is a catalog of off-the-shelf datasets spanning different domains and task complexities. Each comes with a free, ready-to-use demo sample; where a full production corpus is available, the dataset page describes the complete dataset and how to license it. Each dataset includes:
  • Environment — the simulated world state (MCP server snapshots, databases, or filesystems) that the agent operates in
  • Data — generated samples including intents, datapoints, evaluators, and reference payloads

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Available Datasets

APEX Agent

Professional knowledge work across investment banking, law, and management consulting — synthesized from scratch inspired by the APEX benchmark.

Tau2-Bench

Customer service dialogs across airline, banking, and retail domains with multi-turn function calling.

Google Workspace

Everyday Google Workspace tasks — managing emails, calendars, sheets, and contacts across diverse personal and professional scenarios.

OpenClaw

Agentic coding and tool-use tasks across productivity, code intelligence, search, creative synthesis, and safety — built on WildClawBench.

Enterprise Database

Enterprise database operations with realistic schema and query scenarios. Coming soon.

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Download

The free demo samples are hosted on Hugging Face: 
# Download everything
hf download jindidi/eigendata-demo-data --repo-type dataset

# Download a specific dataset
hf download jindidi/eigendata-demo-data --repo-type dataset --include "tau2_bench/*"

Browse on Hugging Face

View and download all demo samples

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License

The demo samples are released under CC BY-NC-ND 4.0.
  • For demonstration and evaluation purposes only
  • No commercial use
  • No redistribution or derivative works
  • No use for model training
Full dataset corpora are available for commercial licensing, including model training — see each dataset’s page or contact support@eigenai.com.