AI Twin
AI Twin is a paid, private personal AI memory layer designed to store and organise information from a user's life and practice. According to its homepage, users can bring documents and PDFs, photos and screenshots, voice notes, typed notes, forwarded email, onboarding answers, WhatsApp chat exports, and social data exports. AI Twin types and logs this material, keeping it in the [ADDRESS] and EU, and states that nothing reaches into user accounts without consent. The service is positioned as model-agnostic: it sits above AI assistants such as Claude, ChatGPT, Gemini, or a local model. Users can keep their memory in AI Twin and connect the assistant they already use, so that changing the underlying model does not mean losing the memory. It supports hybrid retrieval combining typed lookup for precise facts with vector search for fuzzier recall, and organises memory entities into categories including People, Documents, Facts, Events, and Episodes. AI Twin emphasises privacy and control. It describes row-level isolation at the database, an append-only audit log, storage in the [ADDRESS] and EU, export and delete options, and a policy of not selling data or training on it without consent. Captures wait for user confirmation, and wider integrations roll out behind explicit consent. The product is not always-on and captures only what the user asks it to capture. The tool also includes workspaces for personal and business scopes, smart tasks such as Daily Brief, a smart inbox for forwarding email to inbox.ai-twin.app, and support for more than 100 languages. It is available as a paid SaaS product with an on-device demo for memory ranking.
- Category
- AI/ML
- Pricing
- Paid
Problem solved
Personal knowledge is scattered across documents, messages, inboxes, photos, and voice notes, and most AI assistants retain memory only inside their own product. AI Twin addresses this by providing a private, model-agnostic memory layer where users can store and type what matters, then retrieve it through the AI assistant they choose without being locked to one vendor or losing context when they switch models.
Use cases
- Store personal documents, PDFs, and letters as typed, searchable memory
- Forward emails to a smart inbox to turn them into structured memory
- Import WhatsApp chat exports and social data exports for later recall
- Ask an AI assistant to retrieve facts, people, events, and documents from a governed memory layer
- Maintain separate personal and business workspaces with scoped access
- Use voice notes, photos, and screenshots as inputs for memory capture
- Export or delete memory at any time while switching between AI models
- Run a Daily Brief or tidy memory tasks to keep personal knowledge organised
Audience
- Business Users
- Hobbyists
- Enterprise
Pros
- Model-agnostic memory layer lets users swap AI assistants without losing stored context
- Typed memory entities and hybrid retrieval support both precise lookup and fuzzy recall
- Privacy-focused controls include row-level isolation, append-only audit log, export and delete options
- Accepts diverse inputs such as documents, photos, voice notes, email, and chat exports
- Separate personal and business workspaces with scoped viewer access
Cons
- Paid product with no free tier mentioned in the supplied homepage
- Requires manual input and explicit confirmation; not an always-on capture tool
- Integrations are limited and roll out gradually behind consent
- Dependent on external AI assistants or models for chat and retrieval unless using a local model
- Some trust and storage details rely on placeholder text in the supplied page snapshot
Official website: https://www.ai-twin.co.uk/
Canonical LambdaBase page: https://www.lambdabase.com/tools/ai-twin