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Enterprise Layer Intelligence
Categories/Knowledge Management/Prifina
Prifina

Prifina

Founded 2018

Store personal data and context across AI models

Pricing model

Free Trial

You can use Prifina to hold your personal data, context, and memories in one place while connecting to different AI models. It lets you store information from calendars, files, and messages on your own device or private servers without handing raw records over to third-party providers. You can create an AI Twin to answer questions from approved notes, set strict sharing rules, and run assistants like Souvéa to organize your daily schedule. This approach ensures your personal context remains consistent whenever you change underlying models.

What Prifina does

Connect personal calendars, messages, and health data to AI assistantsGenerate cited responses to public inquiries using an AI TwinSelect processing locations between local devices, private infrastructure, and cloud environmentsCreate shared collaboration spaces with selective data permissionsSummarize daily messages and notificationsSwitch AI models used for planning, research, and communicationPersistent personal data storage that keeps files, calendar, and health records togetherInterchangeable model support allowing users to switch AI engines without losing personal contextAI Twin creator to answer external questions strictly from approved sources and citationsChoice of data storage and processing across personal devices, trusted clouds, or private infrastructureShared Spaces for contributing selective context to groups while keeping remaining data privateGoverned organizational environments to separate corporate policies from personal private context

Pricing breakdown

Pricing model: Free trial

PlanList price
Base$24 / mo
Base (paid yearly)$240 / yr total
Pro$99 / mo
Pro (paid yearly)$990 / yr total

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Prifina, personal data layer, AI memory, personal AI, Souvéa, AI Twin, context management, data privacy, edge computing, decentralized data, user permissions, personal data space, AI model interoperability, governed computing, local AI processing