An AI model of how your executive actually thinks.
Trained on their writing, decisions, meeting notes, and frameworks — a private system that drafts responses, reviews proposals, and pre-checks decisions in their voice. They stay the decision-maker. The twin scales their judgement to everywhere they cannot be.
Discovery call → data-access scope → private twin in 6–8 weeks.
Built for chiefs of staff, execs, and founders running beyond their bandwidth — not for replacing leadership, for extending it.
Private by default · on your cloud · no external training · senior engineering team
Executive bandwidth is a structural tax.
Off-the-shelf AI does not solve it. Here's what has to be different.
The exec is the bottleneck
Decisions, proposals, and responses all stack in one inbox. Half of the organization is blocked on one calendar.
Their judgement does not scale
The team needs to know how they would think about something. The exec cannot review every draft, every deal, every email.
Generic AI gets it wrong
Off-the-shelf LLMs write in nobody's voice, reference nobody's priors, and miss the specific frameworks your leader uses.
Data is everywhere
Their thinking lives in emails, Slack, Notion, Google Docs, recorded calls. No single tool sees all of it.
What a digital twin engagement includes
Private AI system. Your cloud. Your data. Your executive in the loop.
- Secure ingestion of emails, docs, meeting notes, and call transcripts
- Fine-tuned or RAG system matched to the exec's decision patterns
- Review-and-approve interface — exec always sees drafts before send
- Evaluation harness measuring voice match, accuracy, and drift
- Role-based access: who can ask the twin what
- Deployed on your cloud, no external training on your data
Scope before we sell you anything.
Free first steps before you commit.
Discovery call
Walk through what the exec is bottlenecking, what data is available, and which decision loops would benefit from a twin.
A clear-eyed read on fit — and on what we would not automate.
Scope and data review
Two-week scoping: data access, security model, eval plan, and fixed-price build proposal.
A plan your legal and security teams can sign off on.
Build and calibrate
Ingestion pipeline, fine-tuning or RAG, review UI. Weekly calibration sessions with the exec until voice, accuracy, and framework match.
A working twin in the exec's voice, running on your infrastructure.
What a production twin looks like at the exec level.
Growth-stage CEO, 200-person org, inbound volume at the exec level overwhelming the chief of staff
The problem
CEO was authoring all investor updates, all strategic proposal reviews, and all board prep personally. Chief of staff team was bottlenecked on CEO turnaround time.
The outcome
Private twin trained on 3 years of CEO writing, board decks, and meeting notes. Drafts investor updates and first-pass strategic proposal reviews. CEO edits, never delegates blind.
Got an exec who is the bottleneck for everything? Let's explore.
Start the conversationCommon questions
Is this an AI clone of a person?
No — and we build it that way deliberately. It's an AI model of how the exec thinks, used as a drafting and review tool. The exec always approves outputs. We do not build autonomous 'AI CEOs' pretending to be humans.
Is the executive's data private?
Yes. Twin runs on your cloud (AWS/GCP/Azure) behind your auth. No training on your data by any external vendor. Raw data never leaves your environment.
What data does it need?
Typically: 2–3 years of emails, written artifacts (docs, memos, updates), meeting transcripts if available, and the frameworks they use. We work with the data you have — we don't demand more.
Who can access the twin?
You decide. Common pattern: exec + chief of staff have full access, leadership team has scoped access to specific decision domains, everyone else uses the output, not the model.
What does it cost?
Typical builds run $200–500k, fixed price, depending on data scope, integration surface, and accuracy targets. Scoping and data review are free.
Fine-tuning or RAG?
Usually RAG with carefully-designed prompting first, fine-tuning only when voice accuracy requires it. We start with the lighter-weight approach and escalate only when measurement justifies it.
Is this the right fit?
Good fit
- Executive bandwidth is a known, measurable bottleneck
- Ample written history and decision artifacts to train on
- Strong chief-of-staff or operations counterpart to own the twin
- Budget for a $200–500k engagement
Not a fit
- Seeking to replace the executive or operate without approval
- Exec does not write, decide, or review in ways we can train on
- Insufficient historical data or governance to work from
- Budget below ~$150k
Got an exec who is the bottleneck for everything?
30 minutes with a CTO and a data-engineering lead. Bring the exec, the situation, and the boundaries.