Enterprise data for training AI agents

AI agents that do business work need examples of that work: what a person saw, what they did in which system, and how it turned out. Licensed enterprise data supplies those examples from operating companies, including workflow histories, support tickets, screen recordings and the procedures teams follow.

Last updated October 3, 2026

Request data

Why enterprise data

Public agent benchmarks such as Mind2Web, WebArena and OSWorld contain hundreds to a few thousand tasks, built on consumer websites, simulated environments or crowdworker demonstrations. They’re good tests but thin training data for enterprise work.

Real company records add the parts agents struggle with: messy context, exceptions to policy, handoffs between people and systems, and outcomes that show whether the work was done right.

Relevant data

Data	Category	Modality	Availability
Task histories with context, actions and outcomes Work items from request to completion, with each action taken and the result.	Operations and workflows	Structured data and text	On request
Screen recordings of real software workflows Recordings and event logs of people completing real tasks in business software.	Operations and workflows	Video and event logs	On request
Helpdesk ticket threads with resolutions Multi-turn tickets with internal notes, tags, status history and the final resolution.	Customer support	Text with structured metadata	On request
SOPs, runbooks and playbooks Step-by-step procedures teams actually follow, with versions and owners.	Documents and knowledge	Documents	On request
Slack and Microsoft Teams workspace archives Channel and thread history with reactions, files and bots over several years.	Chat and email	Text and files	On request
Accounts payable invoices with coding and approvals Vendor invoices with GL coding, approval chains, exceptions and payment status.	Finance and accounting	Documents and structured data	On request
Pull requests with code review threads Diffs, review comments, requested changes, approvals and CI results for each change.	Software engineering	Code and text	On request
CRM pipelines with won/lost outcomes Accounts, opportunities, stage changes and activities through to the final outcome.	Sales and CRM	Structured data and text	On request

What to include in your request

The processes or job roles the agent should handle
The systems involved (for example ServiceNow, Salesforce, NetSuite)
Whether you need outcomes, step-level actions or both
Volume, history and how current the data must be
De-identification and exclusivity requirements

Questions

What data is best for training enterprise AI agents?

Records that capture the steps of real work and its outcome: task histories with actions and decisions, tickets with resolutions, and screen recordings of software tasks. Procedures (SOPs) add the rules the work was supposed to follow.

Can I get data from a specific industry?

Yes. Name the industry in your request; SourceX looks for companies in that industry that hold the data and can license it.

Need this data for a model?

Describe what you need: domain, volume, history, format and licensing terms. SourceX looks for companies that hold it and can license it.

Request data Talk to SourceX