Build a Digital
Double Organization
Coordinated decisions with speed and confidence.
We do not replace the people who decide.
We give their judgment a safe way to scale.
The problem
AI didn’t eliminate work — it overloaded decision‑makers.
The overload
The cost
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).
The solution
We build a TRUSTED Double for each key person. Together they collaborate to prepare and make decisions on your behalf.
At 20 decision-makers: 190 possible conversations — or 20 connections to one DD Core.
Value proposition
From one call after another to all at once with no delays.
Our approach
Everyone copies your face or your knowledge. We copy your judgment.
The trust gap
What we copy: the insight of the call behind the action
Cisco, “The Agent Trust Gap,” March 2026 (survey of senior IT and security leaders) · Microsoft Work Trend Index, 2023.
Differentiator
We calibrate your Double to make your exact judgment calls; rehearse and test it in coordination with other Doubles.
Practice
Run real workflows in the Workflow Gym and score every artifact.
Simulate and test
Seat the Doubles in a simulated meeting.
- The Mirror
- Investment Committee
- New Strategy Launch
- Crisis War Room
Set the limits
Release it within your authority matrix.
Enterprise grade · privacy & security
DD Platform — a scalable decision layer for the enterprise.
Your private cloud (AWS · Azure · GCP) · full data isolation · AES-256 at rest · TLS 1.3 · customer-managed keys
by design
The moat
The longer it runs, the more intelligence it compounds.
- 01Policy mappings + employee IP
- 02Role permissions
- 03Workflow histories
- 04Connector schemas
- 05Approved evidence + outcomes
Landscape & competition
Trusted digital collaborators, not another co-pilot or agent platform.
youConsults expertsSimulates workflowsGoverned writesOne interface
Assessment based on each product’s public capabilities, October 2026.
Market size
100 interviews, 9.7M middle-top managers — a $61B market.
| Vertical | First wave (SAM) | Interviews |
|---|---|---|
| Investment & wealth | 677K | 14 |
| Management & strategy | 1.08M | 5 |
| Legal first wedge | 1.37M | 22 |
| Accounting & tax | 1.60M | 3 |
| Insurance | 1.11M | 11 |
| Executive teams | 3.89M | 45 |
| 6 verticals | 9.72M | 100 |
Sized bottom-up
US jobs, 2025: BLS Occupational Outlook Handbook (Aug 2026); ABA Profile of the Legal Profession 2025. Assumes 1 in 4 is a senior decision-maker, at $25k per Double.
Business model · base case
From one workflow to $50M ARR in year four.
Expand within one account
Grow company-wide
Gross margin
CAC per account
4-year gross LTV
Customer ROI
Base case — plan assumptions, not results. Benchmark: Bessemer AI “Shooting Stars” average ~$3M → $12M → $40M → $103M ARR in years 1–4 (State of AI 2025); a16z median enterprise AI startup $2.1M ARR at month 12; enterprise NRR median ~118%, top quartile ~130%. New accounts 3 + 13 + 45 + 110, 8% of accounts lost each year (active 3 → 16 → 60 → 165). Each account: a paid PoC of 4–6 Doubles becomes a team of 10 in year 1, then 15 → 20 → 24 Doubles; net revenue retention 138% → 134% → 132%. CAC: $75k forward-deployed PoC + $75k sales and marketing = $150k; payback $150k ÷ ($250k × 70%) ≈ 10 mo. LTV: 70% × ($250k + $375k + $500k + $600k), churn-weighted = $1.04M. ROI: $250k salary at 70% of total pay (BLS) = $360k; $25k = 3 of 42 hrs; 37% of time on decisions × 58% ineffective (McKinsey) = 9 hrs; 9 − 3 = 6 hrs net, 9 ÷ 3 = 3×; at 50% recovery, 1.5×.
Team
The team behind Digital Double.
Managing Partners
Engineering
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
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
Ivan Manzhetov
Chief AI Engineer
Richard Popov
Lead Front-End Engineer
Alexey Dyakov
Senior Back-End & Voice AI Engineer
Advisors & Business Associates
Sudeep Badjatia
CEO & Chief AI Architect, Valutics
- Advises Fortune 100 on AI
- Cloud patent holder · VC advisor
- Cornell MBA
Chinat Yu
Founder, Quest2Learn
- ex-Microsoft Research, gen AI
- Stanford LDT · MLH Top 50
- CS, Johns Hopkins
Li Jiang
Director, Stanford AIRE Program
- Teaches robotics & AI at Stanford
- CES Best of Innovations winner
- PhD, McGill
Dr. Paul Kim
CTO & Associate Dean, Stanford GSE
- Designs learning technologies
- National ed-tech advisor
- Saudi Arabia · Rwanda · Uruguay
John Mitchell
Professor of CS, Stanford · HAI
- ex-Vice Provost · ex-CS Chair
- 250+ papers · 30k+ citations
- PhD, MIT
GTM
Forward-deployed paid pilots. Then a firm-wide Double platform.
Design partner
- map one high-value workflow
- build the first Doubles
- set trust + governance rules
Paid PoC
Pilot team
- per-Double seats
- workflow simulator
- internal expert Double graph
Software + services
Firm-wide layer
- firm-wide Double teams
- released workflows
- client- and counterparty-facing action
Platform ARR
paid PoCsper-Double licences + outcome-linked fees →
The ask
Raise $5M to prove the first repeatable deployment.
18 months of runway
What the round proves
- 3 paid design partners
- Fidelity measured on live decisions
- 1+ production conversion, unit costs proven
- Seed-ready metrics: cycle time, margin
Human judgment, turned into software.
We do not replace the people who decide.
We give their judgment a safe way to scale.
See it live → itsbettertogether.io
Alex Stolyarik · CEO · alexsto@stanford.edu
What a Double is made of
How do we build a Double?
Identity & values
Validated personality and values instruments capture stable preferences, priorities and communication style.
Who you areExpert judgment
Structured interviews reconstruct real decisions: the cues, exceptions, risk trade-offs and what mattered.
How you decideMemory & context
Past decisions, corrections, outcomes and authorized enterprise context become a persistent, person-specific working model.
What you’ve livedFidelity benchmark
Hold out unfamiliar cases; compare the Double with its host on decisions, reasons, consistency and correct escalation.
Proof, not promiseWhy it works · the science behind each layer