Less uploading
Meeting details, notes, and questions do not need to leave the device by default.
Long-term vision
Private AI that can go where sensitive work happens.
Trustscribe starts with meetings. The larger goal is private AI memory across the work people do, the tools they use, and eventually the personal devices they rely on.
Local AI
Useful AI should feel close, fast, and under your control.
The more sensitive the work, the less people want to upload it somewhere else. Local AI keeps help closer to the person, their device, and the context they control.
More control
Search, summaries, and answers can happen closer to the person and their data.
Why now
AI moved from storing work to thinking over it.
Many tools already store our files and messages. Now AI reads that work to create answers, summaries, and recommendations. Sensitive work needs a different default.
Remember
People need help remembering conversations, decisions, and follow-ups.
Assist
AI should help summarize, search, draft, and prepare for the next step.
Control
The answer is not less AI. It is useful AI with better control over private context.
Platform
Start with meetings. Build toward private work memory.
A meeting becomes more useful when it connects to the documents, people, calendar events, and open tasks around it.
Capture the meeting
Record, transcribe, summarize, and ask questions without default cloud processing.
Connect the context
Link meetings to contacts, documents, calendars, email, CRM notes, and files.
Help with the work
Draft, prepare, retrieve, and plan while keeping private context under control.
Move into devices
Package local AI into dedicated devices when software alone is not enough.
Hardware direction
A physical AI companion starts with local AI that fits in your pocket.
Taitale is not trying to bolt a chatbot onto every workflow. We are learning how to run useful AI close to the user, inside personal devices people already trust. That is the foundation for building our own hardware over time.
Portable by design
The work starts on phones because they are powerful, personal, and already present in real conversations.
Local AI expertise
Every product step teaches us how to compress, package, and run AI on smaller devices.
Companion hardware
The long-term goal is a trusted physical AI companion for capture, memory, and assistance in sensitive work.
Principles
The hard parts are part of the product.
Local when possible
Sensitive processing should happen on-device or inside controlled environments whenever the workflow allows it.
User control
People need ownership, deletion, portability, and clear sharing boundaries for the knowledge they create.
Supportable claims
Privacy promises must be technically true, legally reviewed, and easy for users to understand.