No. We shouldn't, can't, and won't replace you. Your twin handles the conversations you can't physically be in: the 1:1 someone across the world needs at 3am, the onboarding session you've given a hundred times, the coaching question that comes up every week. You stay focused on the work that only you can do. Your twin handles the rest.

You do. There's a tier of expertise that is completely locked out of the AI revolution because no one has built the trust infrastructure to make it safe. That's us. Your cognitive profile is your intellectual property: not training data for a generic model. You maintain full ownership and control.

AI right now is aggressively mediocre at this. LLMs can give you songwriting tips. They'll tell you about AABA structure and rhyme schemes and emotional arcs. You know what they can't do? Say "that's technically correct but it has no soul," pulling from 20 years of experience. And this isn't just our take. A 2024 study in Science Advances found generative AI improves individual writing while making everyone's writing more alike, and a 2025 evaluation found frontier models changed their answers to agree with the user in more than half of tested cases. A base model is optimized to be everyone's assistant, and being everyone is the opposite of being you. Generic AI is a textbook. We're building the teacher.

Retrieval is part of it, and anyone who tells you otherwise is hiding their architecture. Your twin uses retrieval for facts: what you know, what you've said, what you've written. The difference is what sits on top. Retrieval alone is bounded by your archive, and the best-documented failure mode of retrieval systems is a question the source material never answered. That's exactly when your judgement matters most. So we also build a structured model of how you reason: your frameworks, your decision patterns, your values, how the concepts in your worldview relate. Stanford tested this approach at scale in 2024: AI agents grounded in two-hour interviews reproduced real individuals' answers with 85 percent accuracy, where agents built from demographics or written personas scored around 70. Retrieval for what you know. A cognitive model for how you think.

Most products in this category index what you've said and retrieve it well. Delphi, the best known, describes its own architecture as a knowledge graph built for high-precision retrieval, and the rest of the field runs on persona prompts, fine-tunes on your content, or retrieval over your archive. All of it is anchored to what you've already said. We build the layer above that: a structured model of how you decide, so your twin can handle the question you've never publicly answered. The gap shows up under pressure. Persona-prompted characters drift back into a generic assistant over long conversations, and published research puts persona prompting's ceiling at under 10 percent of what makes an individual's responses their own.

Yes. Twins are available via API, so a twin can sit on any website. The interface can carry your organization's branding, custom domain, and visual identity. Users interact with what looks and feels like your platform. We handle the AI infrastructure underneath.

Absolutely, and this is one of our fastest-growing use cases. Twin panels represent your customer segments for message testing, product innovation, and pricing research. Real-time qualitative research through voice conversations, not static surveys. The science is catching up to the practice: Stanford's 2024 generative-agent research found agents grounded in interviews with real people reproduced those individuals' survey answers with 85 percent accuracy.

Enterprise engagements are scoped by the number of twins, scale of deployment, and level of customization: a setup fee for cognitive profiling and model creation, plus an ongoing platform fee for hosting, analytics, and continuous improvement.

Yes. Enterprise-grade infrastructure with encrypted storage and transmission, role-based access controls, full audit trails, and data isolation between twins.