Full Dataset

Documentation Index

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Inspired by the APEX benchmark, the APEX Agent dataset was synthesized entirely from scratch by EigenData-CLI — every environment, task, and grading rubric is original. The full corpus spans three professional domains: investment banking, law, and management consulting. The scale, difficulty, and benchmark figures on this page cover the investment banking (IB) and management consulting (MC) portion of the corpus — a graded universe of 2,759 tasks.

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What APEX Agent is

APEX Agent is a corpus of long-horizon, finance-domain, tool-using tasks. Each task is a single user prompt describing a deliverable — a number, a memo, a filled-in spreadsheet — paired with a virtual workspace mounted with the relevant files (PDFs, spreadsheets, documents). The agent works the task using tools for filesystem, PDF reading, spreadsheets, document editing, and code execution, then returns a final answer that is graded against a hand-written rubric. Tasks fall into two streams:

• IB (Investment Banking) — questions about company filings, 10-Ks, equity research notes, and deal memos. PDF-heavy.
• MC (Management Consulting) — questions about financial models in Excel: navigating multi-tab workbooks, applying formulas, and producing analysis. Spreadsheet-heavy.

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At a glance

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What’s inside

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Difficulty profile

Every task in the IB + MC universe is sorted into one of three difficulty tiers, based on whether a strong open-weight baseline agent can solve it — where “solve” means a perfect score, every rubric criterion passed: The mix gives the corpus a broad difficulty gradient: a large solvable core plus a substantial hard tier (24%) that defeats both the baseline and current frontier models.

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How challenging is the data

As a reference point, frontier closed-source models were evaluated on sampled subsets of the corpus. Balanced pilot — 100 tasks (50 IB + 50 MC): Hardest-tier subset — 200 tasks: On the hardest tasks, frontier models land around 30%. These tasks demand multi-step domain reasoning, file-format-compliant outputs, and multi-row trajectory handling that current models do not reliably deliver out of the box — which makes the corpus a strong training and evaluation signal.

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Trajectory length

APEX Agent tasks are genuinely long-horizon. The table below summarizes, for baseline agent rollouts, the assistant turns (steps) and tool calls per rollout — shown as mean / median / p90, broken out by domain and difficulty tier:

• IB easy tasks have the longest trajectories (mean 22 steps, p90 45) — reading PDFs and 10-Ks involves many page reads.
• MC trajectories are shorter and more uniform (mean 17–19 steps) — spreadsheet navigation is more direct.
• Tool calls exceed step counts throughout, since a single assistant turn can issue several tool calls in parallel.

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Tool usage

The two streams exercise different tools, reflecting their different source material:

• IB (PDF-heavy) — rollouts are dominated by pdfs_read_pdf_pages, filesystem_search_files, and pdfs_search_pdf, with code_execution_code_exec used for numerical work. Code execution rises in prominence on harder tasks, which demand more quantitative analysis.
• MC (spreadsheet-heavy) — rollouts are dominated by excel_read_tab, excel_list_tabs_in_spreadsheet, and filesystem_search_files, navigating multi-tab financial models. The document tool word_read_document_content also appears on memo-writing tasks.

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Access & licensing

The full APEX Agent corpus — all environments, tasks, rubrics, and trajectories — is available for commercial licensing, including model training. For licensing, contact support@eigenai.com. A free 10-task sample is available now under the CC BY-NC-ND 4.0 license — see Demo Samples.