Ayfie is an AI platform that connects to a company's files, servers and cloud systems, providing a single context layer across assistants, processes and agents. Users can query their organizational knowledge, draft documents and automate tasks with source-verified answers. It serves enterprises needing private, grounded AI tied to their own data.
Product
Ayfie Supervisor
Headquarters
Norway
Funding stage
Public
Last updated
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What Ayfie Supervisor does
The platform comprises an Index that connects and keeps business data current, an Assistant that answers and drafts work using company knowledge, and specialized Agents such as an ERP Agent and a case-management agent. It supports GPT, Claude and Gemini models within a private environment, with integrations into Slack, Microsoft Teams and Copilot, plus an API for custom tools. Built in Norway, it enforces existing access permissions, keeps data in chosen locations, and uses nothing for model training.
What it does
Ayfie Supervisor core capabilities
Index
Connects systems and keeps context up to date
Assistant
Answers and drafts work from company knowledge
Agents
Specialized AI experts for each department
Connectors
Ties Ayfie to every business data source
ERP Agent
Pulls figures, runs analysis, writes reports
Innsynsagenten
Case management with legal-ground drafting
Technical specifications
- Models: GPT, Claude, Gemini
- Integrations: Slack, Teams, Copilot
- REST API
- Hosted in Norway
- RAG-based retrieval
- Source-verified answers
Case studies
No case studies yet
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Trust & compliance
Ayfie Supervisor security at a glance
Security certifications
Named enterprise customers
Pricing details
Ayfie Supervisor pricing
Product videos & screenshots
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Product interface
Ayfie Supervisor Interface
Comparisons
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Transparency
Ayfie Supervisor sources
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FAQs
Frequently asked questions about Ayfie Supervisor
Ayfie is made in Norway and built GDPR-compliant from the architecture up. Customer data stays in the environment the customer chooses, nothing leaves that environment, and nothing is used to train the underlying models.
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