AI operations
Shipping AI is the start, not the finish. unpak keeps reading how work actually happens after you deploy, so you can see what is being used, what is saving the time it promised, and what is quietly drifting, all measured from the work itself.
Watch the impact actually land
The same engine that mapped your work and found the opportunities keeps reading it after you ship, so every solution’s effect shows up in the workflows it touched.
The payoff shows up in the work itself, in the time each run takes before and after.
Read from the work
Impact comes from what people actually do, with idle time stripped out. Nobody has to keep a dashboard up to date by hand.
Drift shows up early
When usage slips or the work starts routing around a solution, it shows in the numbers within weeks.
The same evidence
The engine that found the opportunity is the one that confirms it landed, so the before and the after come from the same place.
See what people actually use
A rollout is not adoption. Because unpak watches the work itself, it counts who really moved to the new way of working and who quietly went back to the old one, person by person, run by run.
Real usage
Logins and license counts tell you who could use a tool. The work tells you who actually does.
Where it sticks
See which teams moved to the new way and which drifted back, down to the person, so you know exactly where to focus.
Enablement that lands
When you can see precisely what is not landing, the fix can be as small as a targeted nudge or a short training session.
Every AI in use, in plain sight
You cannot govern what you cannot see. Because unpak watches the work, every AI tool that touches it shows up, including the ones no one signed off on, and you can see exactly what each one reaches.
Shadow AI, surfaced
The unsanctioned tools people quietly rely on show up on their own, instead of staying invisible until they become a problem.
What each one touches
See which workflows, systems, and documents every tool actually reaches, drawn from real activity rather than a questionnaire.
Policy with proof
Ground your guardrails in what is really happening across the company, not in what people say they use.
Watch your agents in the real work
An agent doing real work deserves the same scrutiny as a person doing it. unpak observes agents in the same stream as your team, so what they actually did sits next to the human work around it instead of hiding behind an API.
Behavior in context
See what an agent actually did inside the workflow, next to the human steps before and after it, not just its own logs.
Drift stands out
When people quietly stop routing work through an agent and go back to doing the step by hand, the change shows against the mapped procedure.
One stream
Agents and people are observed the same way, so the whole picture of how work gets done stays in one place.