Prifina

PERSONAL DATA & INTELLIGENCE LAYER

AI's first era was built by centralizing data.
We are building what comes next.

Prifina is building the personal data and intelligence layer for AI's next era: intelligence that learns with individuals while they control where their data is stored, which AI can use it, where processing takes place and what becomes shared.

Looking for a product? Souvéa and AI Twin.

OUR PRINCIPLE

Liberty. Equality. Data.

People should remain free to control their data, choose the AI that works with it and participate on equal terms.

START HERE

Start with what you want AI to do.

Prifina builds the foundation. Souvéa works for you. AI Twin represents you.

Souvéa

FOR YOUR OWN LIFE AND WORK

Start every day already prepared.

Connect the information you choose, use different AI models, create agents and work privately or with others in Spaces.

Available on iPhone and web.

  • 07:10Overnight messages summarisedReady
  • 08:30Day plan prepared from calendar and healthReady
  • 12:00Share travel details with familyApproval required

AI Twin

FOR SHARING YOUR KNOWLEDGE

You cannot be everywhere. Your knowledge can.

It cites. It stays within scope. It knows when not to answer.

Create an AI version of your knowledge that can answer from approved sources and help people when you are unavailable.

  • More than 2,000 AI Twins created.
  • Used by paying customers.

Souvéa and AI Twin are separate products built on the same Prifina principles. Start with either one, or use both.

A GLOBAL ACADEMIC COMMUNITY

Personal AI is already being explored across leading universities.

Professors, researchers, educators and other individuals associated with universities around the world use Prifina products, primarily AI Twin, to make their knowledge more accessible and useful.

  • Stanford University
  • Northwestern University Kellogg School of Management
  • Cal Poly
  • University of Michigan
  • Goethe University Frankfurt
  • University of Washington
  • Queen Mary University of London
  • University of the Arts London
  • Stockholm University
  • University of California, San Francisco
  • University of Nottingham
  • University of Copenhagen
  • Luiss University
  • Pepperdine University
  • Berkeley City College
  • University of Oulu
  • California College of the Arts
  • KU Leuven

Logos indicate the institutional affiliations of individual users. They do not imply institutional endorsement, procurement or a formal partnership.

THE PLATFORM SHIFT

AI learned from centralized data. The next level may require learning with individuals.

Personal information is copied into every platform, application and AI service. Each one rebuilds part of the person, keeps its own history and creates another dependency. Prifina proposes a persistent personal layer instead, governed around the individual.

Two models for personal data and AI

The first era

One platform holds the relationship.

Files, messages, calendar and health flow inward and stay there. Context is trapped inside the platform, so switching means starting again.

What comes next

The person holds the relationship. Make three choices.

Where personal data is stored and processed
AI capability
Sharing boundary

Personal device · Planning · Personal only

Personal data stays on hardware the person holds, and requests are processed there.

The planning capability is granted permissioned access. It does not take the underlying data.

Nothing crosses the boundary. The space stays entirely personal.

THE MISSING LAYER

Personal intelligence needs an architecture of its own.

01DESIGNED TO ENABLE: Architected and in development. Not a current product claim.

Personal data space

A persistent foundation for personal information, history, permissions and relationships.

  • Files
  • Messages
  • Calendar
  • Health
  • Contacts
  • Travel
  • Plans
  • Personal knowledge
02DESIGNED TO ENABLE: Architected and in development. Not a current product claim.

AI choice

Use different models and capabilities without rebuilding the personal foundation for every service.

  • Planning
  • Research and synthesis
  • Health and wellbeing
  • Communication
03DESIGNED TO ENABLE: Architected and in development. Not a current product claim.

Storage and processing choices

Choose where personal data is stored and where an AI request is processed: personal devices, selected cloud environments, private infrastructure or systems inside a chosen country or region.

  • Personal device
  • Trusted cloud
  • Private infrastructure
  • Chosen region
04DESIGNED TO ENABLE: Architected and in development. Not a current product claim.

Shared spaces

Contribute selected information to a governed shared context while keeping the rest personal.

  • A private group
  • A family
  • A professional network
  • A local area
  • A special interest group
  • A service environment created by a partner

Every layer carries a status badge. The full definition of each label lives on the Technology page.

RESEARCHING WHAT COMES NEXT

The next AI architecture will not be built by one company alone.

Prifina collaborates with the University of Oulu's Future Computing Group to explore personal and distributed AI, edge intelligence and governed computing across devices, regional infrastructure and cloud environments.

WE ARE RESEARCHING: An open research direction. No availability implied.
  • Personal and distributed intelligence

    How intelligence can improve for an individual without that individual's raw context being consolidated into a single platform.

  • Edge and regional computing

    Which parts of a personal AI workload belong on a device, in regional infrastructure, or in a larger cloud environment, and what decides that.

  • AI agent governance

    How an agent's scope, permissions and expiry can be expressed in a way both a person and a system can verify.

  • Permissioned learning

    How learning signals can be approved, bounded and withdrawn instead of being an invisible byproduct of use.

  • Provenance and inspectability

    How a person can see which source produced an answer when several models and processing environments were involved.

  • Shared intelligence without pooling all raw personal data

    How a group can gain shared understanding while each member's underlying personal space stays separate.

INDUSTRY CONVERSATION

Prifina is exploring new models for personal AI with Mastercard.

Mastercard

THE COMPANY

Building the foundation for personal intelligence.

Prifina brings together product development, personal data architecture and research into new models for AI that can work with individuals without requiring one platform to control the entire data relationship.

01

Product development

Souvéa and AI Twin are in market today. They are how the architecture is tested against real everyday and professional use.

02

Personal data architecture

A persistent layer for data, permissions, relationships and learning, designed to outlive any single model or service.

03

Research relationships

Prifina collaborates with the University of Oulu's Future Computing Group to explore personal and distributed AI, edge intelligence and governed computing across devices, regional infrastructure and cloud environments.

LATEST INSIGHTS

The reasoning behind the architecture.

All insights

If AI's next era needs a different foundation, let's build it.

We work with researchers, AI and infrastructure companies, regional partners, investors and service builders exploring new models for personal and shared intelligence.

Investors, researchers, operators and service builders are all welcome.