Business data for AI agents

What AI agent evaluation data from business operations is

Last updated November 1, 2026/Business data for AI agents

AI agent evaluation data from business operations is a set of past cases whose endings are already known, kept aside so someone can see whether an agent fails in the ways the business would notice. The case is not there to teach the agent the answer. It is there to ask the agent to act, then compare that action with what a competent person did, or with whether the real outcome held. If the same case was already inside the material the agent learned from, the comparison is theater. The test has been spoiled by leakage.

A software company's resolved tickets are a familiar specimen. A case opens with a product symptom. A person asks, tries, escalates, and the ticket reaches a coded ending that does not immediately reopen. Held out, that case can show whether an agent skips the question a human asked or invents a fix the product cannot do. The customer's own workspace, pasted into the ticket, is often not part of the test you are allowed to share. What a SaaS company already generates that can train AI is the industry page. How support tickets and chat logs can be licensed is the shelf. This page is about the role of the case as a test.

Evaluation teams are one of the buyer types on which kinds of teams look for company operating data. They are not a promise that such a team wants your industry. How an agent learns from work in the first place is how business data trains AI agents to do real work. The path the test might replay is what an agent trajectory records from real work. A license, if the cases can be offered at all, is what AI data licensing means for a company.

Why a known failure is more useful than another success story

Public writeups keep the wins. Operations keep the reopen, the wrong part, the customer who came back, the lot that failed the second inspection. An evaluation set that is only victories teaches an agent to sound finished. A set that includes the cases the business itself treats as misses shows whether the agent misses in the same places. The point is not a vanity score. The point is a disagreement you can inspect.

Inspectable means a second person can see the outcome without asking the agent. A coded resolution, a hold that was or was not released, a shipment that was or was not recovered. A note that everyone felt good is not an outcome. Teams that evaluate agents walk away from archives that cannot support that second look.

What makes a past case usable as a test

• The ending is in the record and was not typed in after you decided to build a test. Backfilling answers spoils the case.
• The case can be held out. You can point to a slice that was not used to teach, or you can say honestly that you cannot separate the slices.
• The failure mode is one the business recognizes: reopened, wrong escalation, missed check, unsafe shortcut. A novel trick that no operator cares about is a weak test even if it is clever.
• The case can be shown without the fields that are access data, payment instruments, or another party's confidential content. If it cannot, it is not a test case for this marketplace. It is a record to leave closed.

Leakage, in plain words

If the agent was shown the ending, or a near-copy of the case, before the test, a good score does not mean the agent can do the job. It means the agent can remember. Evaluation data is the discipline of not handing over the answer and then congratulating the system for having it. Companies that cannot tell which cases were already shared should not describe a set as held out.

What makes an operations archive a bad exam

• No negative cases. Every ticket in the extract was a smooth close. The test cannot show a miss.
• Endings that were edited for the demo. The historical outcome and the exhibit disagree.
• A single heroic incident offered as if it were a set. One story is an anecdote. Evaluation wants repetition of a recognizable job.
• Customer, patient, or employee content that the check requires you to reveal. A test that only works by exposing a person is a test you should not run in public or in a license.
• Treating a buyer's interest in evaluation as legal clearance. A held-out case can be the right shape and still be forbidden by contract. This page is not legal advice.

How a test set is described

Unlockt, LLC is the operator of Big Data/Little Guy. We do not score your archive, and we do not invent a pass rate. The free check can record whether past work has known outcomes. It is the free data value check, and it does not receive the cases.

A profile can say that a class of work has outcomes and that a held-out split has not been claimed, or that it has been claimed only for a scope you can explain. Buyers who evaluate agents would read that profile. They would not receive the queue in order to grade it on day one. Nearby definitions are in plain definitions for AI data licensing terms. A high opinion of your tickets is not an offer.