Coordinated decisions
made by vetted
Digital Double Teams

A Double for every decision-maker. Together they make the calls between the systems and processes.

01

Coordination

AI systems are fast. The handoffs between people aren’t.

The coordination tax

57%of the working day goes to coordinationcalls, meetings and ping-pong messaging
43%is left for the actual workcreating, not communicating

The manager’s day

40%of a manager’s time goes to their own tasksnearly all (97%) juggle doing and leading
275interruptions a dayone every two minutes

Microsoft Work Trend Index 2023: the average employee spends 57% of their time communicating (meetings, email, chat) and 43% creating — measured across Microsoft 365 users in all industries. Manager time: Gallup 2025. Interruptions: Microsoft Work Trend Index 2025.

More ideas, drafts, options and requests come in and need attention while you are stuck in another meeting.

02

The queue

Every handoff is a queue needing attention.

46 minof actual work
3 h 33 minfrom exception to resolution
workwaiting

Decisions come in sequence, each waiting its turn inside the inbox.

03

The gap

Every kind of workflow gets an AI tool,
but the decision-making coordination stays human.

What firms get today

You → personal copilotsHelp the user with their own work — ChatGPT, Copilot, Gemini.
Inside → in-app agentsAutomate tasks inside internal systems — CRM, OMS, ticketing.
Across → agent orchestrationRoutes work between agents —
ServiceNow AI Agent Orchestrator, Salesforce Agentforce.

The gap

  • only you understand the context
  • only you know who and how to ask
  • only you make decisions to act

Gartner, August 2025: 40% of enterprise apps will include task-specific AI agents by the end of 2026, up from under 5% in 2025.

04

The size

The gap is getting bigger — AI overloaded decision‑makers.

The overload

77%say AI has added to their workloadamong employees using AI
39%spend more time reviewing AI-generated contentamong employees using AI

The cost

$250Min wages lost every yearmanager time on ineffective decisions, typical Fortune 500
56%have to ask someone or book a meetingto get the information they need

Manager time: McKinsey, “Decision making in the age of urgency,” 2019 (n = 1,228). Asking: Atlassian, State of Teams 2025. AI workload: Upwork Research Institute & Workplace Intelligence, “From Burnout to Balance,” 2024 (n = 2,500; U.S., U.K., Australia, Canada).

05

The solution

To solve the problem,
we offer one
Digital Double Core

A coordinated and rehearsed set of policies that connects every decision-maker’s Double.

06

The DD Core

Each person trains a Double. Together they collaborate to prepare and make decisions.

PeopleStay accountable. Make the calls that need them.
DoublesCalibrated on each person’s judgment.
DD CoreOne shared case, state and rulebook.
Enterprise systemsPMS, OMS/EMS, risk, compliance, post-trade.
At 20 decision-makers: 190 possible conversations — or 20 connections to one DD Core.
07

Efficiency

Your Double works with the DD Core and across your tools
testing possible scenarios to bring you one call to make.

PM’s Doubleto the PM

Add $4M to XYZ? It would cross the 5% single-name limit by 0.4%.

Risk DD: inside the VaR budget
Compliance DD: no restrictions
AAdd $4M, escalate to the CRO
BAdd $3.2M, stay at the limit
CWait for the rebalance

You chose B in 7 of 9 similar cases

Approve B
08

No delays

From one call after another to all at once.

09

Category

Everyone copies your face or your knowledge. We copy your judgment.

RepresentationTavus · HeyGen · Synthesia
FaceHow you look and sound
KnowledgeViven · Delphi · Glean
FilesWhat you know and can retrieve
ExecutionServiceNow · Agentforce · UiPath
AgentsWhat tools do when instructed
SimulationSimile · Aaru
CrowdsHow populations behave
RehearsalYoodli · Mursion · Second Nature
PracticeGeneric personas to rehearse with
Cognitive AIDigital Double
JudgmentHow one specific person weighs trade-offs

The trust gap

85% | 5%of major enterprises are piloting AI agents. Only 5% have moved them into production.
40%+of agentic AI projects will be cancelled by end-2027 — on cost, unclear value and weak risk controls.

Acting isn’t the hard part.
Being trusted to decide is.

Cisco, March 2026 (enterprise customer survey) · Gartner, June 2025 (agentic AI project forecast).

10

The judgment

The judgment isn’t the task or ubiquitous AI knowledge — it’s the call.

37%of managers’ working time
goes to making decisions.

McKinsey, “Decision making in the age of urgency,” 2019 (n = 1,228)

What to approve, when to push back, who to escalate to. That is judgment — and it lives in one head.

Digital Double11

Product

A Digital Double is a persistent and evolving model of a specific real manager’s judgment behavior.

Positioning stack

Cognitive AI

Cognitive AI is AI that models how specific people reason and decide — why its host makes the call, how they weigh it, and how the room will react. It sits above copilots and agents, which generate content or take actions.

It brings four categories into one layer:

  • Enterprise AI assistants & agents
  • Human digital twins
  • Behavioral simulation
  • Governed delegation

Digital Double

A new approach to superintelligence: a persistent, governed model of one person’s working judgment that collaborates with other Doubles. It is built on three commitments:

  1. 1
    Models a real personThe unit is named human judgment, not a job title.
  2. 2
    Proves itself in rehearsalEvery workflow earns confidence before deployment.
  3. 3
    Acts with governanceApprovals, limits, escalation and audit are product features.
12

Governance

Your delegation-of-authority matrix, made executable.

Order size
Limit headroom
Broker & vendor terms
Allocations
Investor disclosures
CIO’s Double
Approves · up to $25M
Suggests
Suggests
—
Never
Trader’s Double
Approves · up to $5M
Escalates
Approves · standard terms
Suggests
Never
PM’s Double
Approves · up to $2M
Approves · up to 2%
Drafts
Suggests
Never
COO’s Double
—
Watches
Suggests
Approves · standard splits
Drafts
CCO’s Double
—
Escalates
Approves · standard NDAs
—
Watches
Approves — acts within the limitDrafts — prepares it, a human signsSuggests — a human decidesEscalates — routes it to the ownerWatches — predicts, touches nothingNever delegated

Every limit is set by the leader it belongs to, mirrors the authority matrix your investment and risk committees already approve, and every action is logged.

13

Product

Your Double has 3 jobs + 1 responsibility.

01Works with you

Personal operating layer

Ask job-specific questions, draft work, compare options, prepare decisions and reflect — without learning a new interface every time the AI stack changes.

02Consults for you

Company expertise network

Your Double can ask the authorized Doubles of top managers and specialists for context, precedent and judgment — and be borrowed by others to participate in simulation trainings.

03Acts for you

Vetted digital operator

Once your rules and policies are tested, the Double can send, decide, coordinate or represent you within explicit limits — escalating what still belongs to you.

04Coordination

Every Double plugs into one coordination layer — the DD Core — so the whole company’s Doubles work as one: sharing context, routing each case to the right person and staying inside your systems, rules and permissions.

14

01Personal operating layer

Your Double learns every and any other tool for you, so you don’t have to. The last AI interface you’ll ever need.

Talk to one AI, in your own words. No prompt craft, no new interface per tool.
It operates the rest. Your Double drives the tools you already pay for.
It decides like you — because it was calibrated on you, then proven in rehearsal.
15

02Consults for you

Your Double doesn’t have to know everything. It knows who does.

Ask one place“Can we add to this position today?” “What would our head trader do?” “How did we handle this before?”
Consult the right expertiseThe Double assembles the relevant human judgment, systems and precedent — instead of making you hunt for it.
Keep boundaries explicitExpert Doubles expose only the knowledge, decisions and workflows the company authorizes.
16

03Acts for you

Governed by design.

ConsentYou sign offand can revoke it anytime.
LimitsIt stays in boundsand asks when it can’t.
AuditEvery call is recordedwho, what, why and when.
17

04Coordination

A central decision core for the enterprise.

The application is designed to handle the heavy loads and strict security for large-scale operations.

18

Privacy & data sovereignty

Personal memory stays protected. Runs inside your boundary.

Security & encryption

  • AES-256 at rest, TLS 1.3 in transit
  • Third-party penetration testing
  • Built toward SOC 2, HIPAA and GDPR

Private deployment

  • Your AWS, Azure or GCP tenancy
  • Full data isolation per customer
  • Customer-managed encryption keys

Identity & personal memory

  • SAML SSO and SCIM provisioning
  • Memory: you and authorized people only
  • Every access traced, instant revocation

Zero public training. Personal memory, decision models and graphs stay your IP — in your own cloud tenancy.

19

Our approach

We train and test your Double to make your exact judgment calls.

Calibrate

Dual-sided model

A ~25-minute behavioral and professional interview builds your Double.

Rehearse

Workflow Gym

Your Double runs your real workflows again and again — while you correct its calls.

Test

Simulation Studio

Edge cases, pressure and hostile counterparts — every run is scored against your own call.

Release

Governed action

Once it clears your bar, it acts — with permissions, limits, escalation and a full audit trail.

Each Double learns from its host, rehearses real scenarios, and proves reliability before it earns authority.

20

Simulation Studio

Rehearse every call before you release it — from one workflow to strategic war games and company-wide simulation.

Investment Committee
LP Redemption Call
The Mirror
Limit Breach
New Strategy Launch
Crisis War Room

Simulation output

Matched your decision86%
Escalated correctly94%
Policy violations0
Ready gateActs with sign-off

The simulator doesn’t make AI feel safer. It generates the evidence needed to release it safely.

From the Digital Double Studio room library. Any room can be recomposed. Simulation output is illustrative.

21

Earned trust

It earns trust the way a new hire does.

It watches real cases, then suggests. It acts only on the decisions it has proven it calls the way you do.

22

The moat

The moat is the company’s decision graph.

Policy mappings + personal IPLimits, exceptions and approval rules become executable objects — with departure rules for personal IP set up front.
Role permissionsThe real decision boundaries between PM, Risk, Compliance, Trading and Ops.
Workflow historiesEvery resolved case shows how this company actually coordinates.
Connector schemasEach integration maps the company’s systems into one decision model — costly to rebuild.
Approved evidence + outcomesA growing record that makes the next case faster to route and safer to act on.
23

Hot

Wherever one expert’s call is the product — and the bottleneck.

Investment and asset management743K US professionals
  • Hedge funds and asset managers
  • RIAs and family offices
  • Investment committees
Management consulting1.08M US professionals
  • Strategy and operations boutiques
  • IT and implementation consulting
  • HR and change advisory
Legal1.37M US professionals
  • Mid-size law firms
  • In-house legal teams
  • Regulatory and compliance practices
Accounting and tax1.60M US professionals
  • PE-backed CPA platforms
  • Tax and audit review
  • Advisory and transaction services
Insurance126K US professionals
  • Commercial underwriting
  • MGAs and specialty carriers
  • Claims and reinsurance
Executive teams292K US professionals
  • Founder-led companies
  • CEO and chief of staff office
  • PE portfolio leadership

US headcounts: BLS Occupational Outlook Handbook, 2025 employment (management analysts; accountants and auditors; personal financial advisors + financial analysts; insurance underwriters; chief executives) · ABA Profile of the Legal Profession 2025.

24

GTM

Consulting-led Pilot.

Phase 1

Design partner

  • map one high-value workflow
  • build the first Doubles
  • set trust + governance rules

Services revenue

Phase 2

Pilot team

  • per-Double seats
  • workflow simulator
  • internal expert Double graph

Software + services

Phase 3

Firm-wide layer

  • firm-wide Double teams
  • released workflows
  • client- and counterparty-facing action

Platform ARR

services-ledrecurring platform revenue →

25

Team

The team behind Digital Double.

Managing Partners

Alex Stolyarik

Alex Stolyarik

CEO · Managing Partner

  • 25 years in Gen & Physical AI, XR and Digital Twins
  • Leads Digital Double at Stanford’s AIRE and LYTICS labs
  • Two exits · CEO of a $7.4B multinational at its LSE IPO
  • Advises Stanford SAL · NSF SBIR grant · GSV Elite 200
  • Degrees from MIT, Stanford and Harvard Business School
Lana Kara

Lana Kara

Managing Partner

  • Venture Partner and DeepTech executive, 15+ years
  • $5B+ in VC and PE deals across the US and Europe
  • Led strategy for a $2B AUM Swiss family office
  • GP of a Digital Twin AI/SaaS venture fund
  • Founder, SK BioScience AI Digital Twin platform

Advisors & Business Associates

Sudeep Badjatia

Sudeep Badjatia

CEO & Chief AI Architect, Valutics

  • Advises Fortune 100 on AI
  • Cloud patent holder · VC advisor
  • Cornell MBA
Chinat Yu

Chinat Yu

Founder, Quest2Learn

  • ex-Microsoft Research, gen AI
  • Stanford LDT · MLH Top 50
  • CS, Johns Hopkins
Li Jiang

Li Jiang

Director, Stanford AIRE Program

  • Teaches robotics & AI at Stanford
  • CES Best of Innovations winner
  • PhD, McGill
Dr. Paul Kim

Dr. Paul Kim

CTO & Associate Dean, Stanford GSE

  • Designs learning technologies
  • National ed-tech advisor
  • Saudi Arabia · Rwanda · Uruguay
John Mitchell

John Mitchell

Professor of CS, Stanford · HAI

  • ex-Vice Provost · ex-CS Chair
  • 250+ papers · 30k+ citations
  • PhD, MIT
26

Next step

The pilot, in three numbers. Measured four ways.

Duration8 weeksMap, shadow, act with approval, measure — two weeks each.
Scope1 workflowDiscount exceptions, vendor renewals, escalations or budget approvals.
People4–6 DoublesThe leaders who own that workflow’s decisions today.

What we measure

Decision latency

days → hours on delegated decision types

PM and analyst hours returned

time back for research and positioning, per desk

Meetings removed

decision meetings that never need to happen

% decisions delegated

share released to act with sign-off or on its own

27

The bottom line

Human judgment,
turned into software.

Digital Double captures how a real person decides, proves that model in simulation, then works in coordination with other people’s Doubles.

Calibrate→Rehearse→Release→Govern
28

Appendix · Architecture

Architecture.

Design ruleEvent-drivenWork starts when something happens in a company system — not when someone remembers to ask.
Design ruleHuman-in-the-loopThe decision case, not the chat, is the unit of work — and a named person signs anything outside a released class.
Design ruleAuditable by designEvery step records who decided, on what evidence and under which permission.
29

Appendix · Methodology

Research-backed foundations.

Critical Decision Method

Developed by Gary Klein for high-stakes fields — firefighting, critical care, aviation. Captures the cues, trade-offs and risk thresholds behind real critical incidents, not hypothetical questionnaires.

CoALA cognitive architecture

Grounds the Double in structured working memory, long-term episodic recall and policy-bound action — so authority can’t drift (Sumers et al., 2023).

Generative agents

Persistent memory, retrieval and reflection keep a simulated person coherent over time — the basis for Doubles that remember what their host has seen (Park et al., 2023).

Cognitive Task Analysis

Structured interviews and observation that surface the tacit knowledge experts can’t easily put into words — the mental models, cues and strategies behind their calls (Crandall, Klein & Hoffman, 2006).

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