The decision science company behind Pressure Room.
PAVNESS works with founders, CEOs and corporate executive teams to preserve and strengthen consequential judgment when facts, people, AI or leadership change.
When an AI-influenced call goes wrong, or a transition fails, someone has to answer for it — and usually nobody can. The work moved through four people, each of whom approved it, and none of whom experienced themselves as deciding it.
PAVNESS works on that gap directly. In a constructed living-company simulation, leaders make consequential calls, see what those choices create and make the operating rules explicit: whose call it is, what evidence is enough, when escalation happens and what AI may do.
Where we sit in your stack
Software systems log data, governance tools track model inventory, and consulting firms bill hours documenting processes. We measure whether a named human can defend the judgment driving the system.
“Is the AI system working correctly?”
“Can a named human defend the call under pressure?”
- A decision somebody can still explain in six months
- A named owner for it, agreed out loud
- A short routine a reviewer runs before signing
Software records what happened. We test whether a person can explain it.
How it works
We don’t sell implementation projects, software subscriptions or anything that requires access to your systems. The work is a constructed decision simulation — the cases are built, not borrowed, so nothing of yours has to leave the room.
| Act | What happens | What the room leaves with |
|---|---|---|
| First | You decide, on the evidence in front of you, before any machine participates. | Your own baseline, in your own words |
| Then | The information changes, the recommendation gets more confident, the clock shortens — and you decide again. | What actually moved your judgment |
| Finally | The room agrees what AI may do here, who owns the call, what reasoning stays visible, and when to escalate. | A standard, plus THINK — the routine a reviewer runs before signing |
One instrument, three depths
We apply one discipline and sell one instrument, at three depths.
The Workslop Tax Self-Diagnostic
What AI rework is costing you, on your own headcount and your own hourly rate.
Published research supplies the hours. You supply the two numbers that make it yours. It also asks what your signature currently sits on.
When AI Can Think, Who Decides?
Make the invisible visible.
A constructed simulation shows a room how its own judgment moves when a confident machine participates. USD 5,000 for the first three sessions booked before 31 October 2026, USD 7,500 after.
The practice format
Make behavior observable.
People decide under pressure, defend the call, reconcile where two of them decided the same case differently, and apply the standard to their own recurring work. A half day, at USD 17,000, makes those expectations shared across a whole function.
Why executive sponsors work with us
| Legacy management consulting | PAVNESS | |
|---|---|---|
| Timeline | Three to six months | Fifty minutes to a half day |
| Output | A 100-page static deck | A standard the group states out loud, practised under pressure |
| Business model | Profits by selling the costly fix | Fixed scope — we don’t sell software remediation |
| Focus | High-level process mapping | Live testing of named decision owners under pressure |
Scope and operational boundaries
We do not sell remediation software. We don’t profit from building or reselling software platforms, and there is no remediation revenue riding on what we find. A firm that profits from the fix has a reason to be careful about the finding. We don’t have one.
We do not replace legal or compliance. We measure human judgment and decision ownership. Your internal counsel and compliance teams keep full control, authority, and risk ownership.
Defensible evidence, not sign-offs. We observe how a consequential decision is actually made — on the day it is run, in the scenarios it tests. We do not assess, score or name an individual, and we never certify, approve, or declare a system safe to deploy. Findings describe what was observed at a point in time — they assign no blame and issue no instructions. We provide the defensible evidence boards, PE partners, and leadership teams need to make their own call. Whether a specific organization is covered by any rule, and what it must do, is a determination for its counsel. This is not legal advice.
Founder and background
Founded by Pav Lertjitbanjong — a Thai-American decision scientist with more than twenty years inside Fortune 500 and global firms, most recently leading strategic analytics.
PAVNESS was built on a single insight: AI can generate the work, but only a human can defend the call.
A decision map tells you who is supposed to hold something. Only pressure tells you whether they can.
Bring one real decision.
Bring a workflow where AI already participates and a person who signs off on it. Fifteen minutes is enough to tell whether this belongs in your organization. If it is not a fit, we will say so on the call rather than send a proposal.