Target 40% Fewer Meetings. Keep Judgment Moving.
Your meetings exist because judgment lives in a few calendars. WisdomTwin brings that judgment to the decision while the question is live, and a named human still signs.
A pilot target, measured against your own baseline at a 12-week checkpoint. Not a guarantee.
Harvard Business Review, 2022: across 76 companies, where meetings fell 40%, employees rated their productivity 71% higher and their satisfaction 52% higher. Published research, not a WisdomTwin result. MIT Sloan Management Review · Harvard Business Review
The decision is ready. The person is not.
- Tuesday
The credit exception is ready.
- Thursday
The one person who can approve it is free.
- Next month
The committee meets.
The facts are searchable in seconds. The judgment lives in a few senior people's calendars, and regulated teams cannot paste the work into a public chatbot. So the meeting stays, and the decision waits for it.
AI made answers instant. Enterprises still make decisions at calendar speed.
The cost of waiting is already on your payroll.
per employee per year spent on meetings
Otter.ai and Prof. Steven Rogelberg, UNC Charlotte, 2022
of that on meetings employees say they could skip
Otter.ai and Prof. Steven Rogelberg, 2022
a year in unnecessary meetings at companies with 5,000+ employees
Otter.ai and Prof. Steven Rogelberg, 2022
a year consumed by one weekly executive committee meeting at one large company
Bain & Company, 2014
Published research, not WisdomTwin results.
Price one recurring meeting.
Example inputs. Replace them with yours.
- Hours per year
- 384
- Cost per year in USD
- USD $46,080
- Hours in scope at the 40% target
- 153.6
Your inputs, simple arithmetic over 48 working weeks. Not a WisdomTwin estimate, saving or result.
In a regulated firm, the meeting is where judgment lives.
Cutting meetings works until a decision needs someone's judgment. Then the meeting comes back. The credit exception gets weighed, checked against policy and signed in that room. Cancel the room and the decision has nowhere to go.
Move the judgment to the decision, and the meeting becomes optional.
A paragraph can explain a situation. A workflow still needs a typed decision: a bounded action, evidence, uncertainty, policy result, authorization and a named human release.
WisdomTwin.ai is being built around that contract. The model proposes a bounded recommendation. A policy layer applies explicit rules. The accountable human keeps the call.
This is the difference between a paragraph that sounds plausible and a decision a regulated workflow can inspect.
Bring the judgment to the decision, not the people to the room.
One-Press Huddle
Open the decision when it arises and convene the roles it needs, without creating another calendar dependency.
Role-specific AI Judgment Twins
Bring forward the authorized policy, precedent, thresholds, exceptions and escalation rules a role uses to exercise judgment. An AI Judgment Twin is not a cloned person and does not act with independent authority.
Trust Layer
Designed to keep provenance, source permissions, version history, human review, escalation and audit records in the decision path.
- 01
Ingest
Connect the evidence a role is authorized to use, inside the enterprise's data and identity boundaries.
- 02
Twin
Structure that evidence into role-specific principles, thresholds, exceptions, precedent and escalation paths.
- 03
Operate
Use that judgment in a One-Press Huddle or asynchronous decision thread. The system recommends, escalates or safely declines, while a named human retains authority.
The twin recommends, escalates or safely declines. A named human decides.
What a twin is, and is not
| A twin is | A twin is not |
|---|---|
| Role-specific judgment built from authorized evidence | A cloned person |
| The thresholds, exceptions and escalation rules of a role | A chatbot that guesses |
| Cited evidence behind every recommendation | A black box |
| A named human who approves, declines or escalates | An autonomous decision-maker |
| Designed for private cloud, VPC or on-premises deployment | A public tool you paste work into |
Watch a Judgment Twin handle a live decision.
The Named Call (78 seconds)
Watch a Judgment Twin get a decision to the person who can put their name on it.
One role. One recurring decision. A 40% meeting target.
- 01
Baseline
We count the internal meetings in the workflows in scope, with your team, before anything is built.
- 02
Twin
We build one role's judgment from authorized evidence. A named human signs every decision.
- 03
Checkpoint
At 12 weeks we measure against your baseline. The target is 40% fewer internal meetings in that workflow.
What you get at week 12: Your baseline. The count after. The decision record behind every call.
A target, not a promise. Scope and terms are agreed on a call.
Speed a regulated enterprise can defend.
Designed for regulated enterprises.
- Sovereign deployment patterns: private cloud, customer-hosted, on-prem, hybrid, air-gapped, evaluated in pilot scoping.
- Authorized data and identity boundaries agreed before anything is ingested.
- Role-based access, provenance, and version history around every answer.
- Human review and explicit escalation when evidence or authority runs out.
- Configurable retention and audit records of what was decided and by whom.
- Deployment design targets on-premises or customer private cloud, subject to pilot acceptance testing. Air-gap is a separate unverified acceptance profile.
Designed for on-prem, on-device, and customer private cloud patterns. Patterns are scoped in pilot. None is claimed as a certified production air-gap today.
Start with the decision that waits longest.
Banking
BeforeCredit exceptions wait for committee availability.
AfterThe decision package is assembled while the question is live.
Insurance
BeforeClaims wait while context and policy limits are reconstructed.
AfterClaims move with evidence, limits, and escalation attached.
Healthcare
BeforePolicy interpretation waits for the next governance meeting.
AfterPolicy interpretation arrives with its evidence, for administrative decisions.
Government
BeforeProcurement determinations wait between reviewers.
AfterDecision support starts immediately, with authority still named.
Legal
BeforePartners become the bottleneck, and recurring determinations wait.
AfterInstitutional judgment is available, and exceptions reach a human.
Built and working, ready for a first pilot.
- One-Press Huddle: multi-speaker audio huddles, recorded and transcribed.
- Evidence timelines and decision records, with citations.
- Human validation, confidence breakdown, policy denial and safe decline.
- A held-out evaluation framework for judgment fidelity.
- Five founder-built industry demonstrations.
- Open-access working papers on judgment latency.
We used our own twin to win a government RFP for Talent Lab. Talent Lab's CEO said on our podcast that the win generated USD $5.5M in revenue for her company in 2025. This is a client outcome on the record, not WisdomTwin product revenue.
What is live, what is validated, what is a target
Live today
- Public product experience and website
- Founder-built sample demonstrations
- WisdomTwin Research Library and public working papers
- Trust Layer control specification and pilot protocol
- Bounded pilot scoping process
Validated in a pilot
- No customer or pilot outcomes are published here yet.
Target / subject to validation
- Customer private cloud, on-premises, hybrid and air-gapped deployment patterns
- The 40% meeting-reduction target
- Production certifications or regulatory attestations
- Customer outcomes and measured productivity results
A target, architecture proposal or demonstration is not a customer result.
The work was ready Tuesday. The calendar said Thursday.
I spent twenty-eight years selling into P&G across 21 brands, Apple, Microsoft, General Motors, Marriott and Wave, across 15 countries and 5 continents. The work was ready Tuesday. The calendar said Thursday. Those companies were my classrooms, not WisdomTwin.ai deployments.
Decisions should not wait for the room. We don't replace judgment. We remove the wait.
The wait is a prepared decision sitting until the next meeting. Governance, required approvals and named human authority remain.
I spent twenty-eight years in enterprise rooms where Tuesday's prepared work waited for Thursday's meeting. I am building WisdomTwin.ai so the decision can move with evidence, permissions and human authority intact.Read Roman's founder story
Questions
- Will it get rid of all our meetings?
- No. Some meetings do important work. The pilot target is 40% fewer internal meetings in the workflows in scope, measured against your own baseline at a 12-week checkpoint. We go after the meetings that exist only because the right person is hard to reach.
- Do you promise the 40%?
- No. It is a target we measure with you, not a result we claim. Your baseline comes first, then the 12-week checkpoint. Roman covers the terms on a call.
- Are you cloning people?
- No. A clone reproduces a person's voice and opinions. A twin models how a role decides inside its authorized domain, and it cannot take on anyone's accountability.
- How is this different from Copilot or enterprise search?
- Search and chat retrieve information. A judgment twin is organized around the decision: the evidence, the thresholds, the possible exceptions and who must review it.
- Who approves the decision?
- People do. Nothing is final until a named human approves, declines or escalates it.
- What happens when the twin does not know?
- It declines and escalates instead of guessing.
- Can our data stay inside our environment?
- WisdomTwin is designed for private cloud, VPC or on-premises deployment. Your requirements are validated during pilot scoping.
- What does it cost?
- Every engagement is scoped to one role and one decision. Roman covers that on a 20-minute call.
Name the meeting you would cut first.
Bring one recurring decision. In 20 minutes, Roman maps where the judgment waits and what a 12-week pilot would measure.