The complete framework for implementing Private AI
Becoming AI-driven is a challenge for most organisations. This framework supports IT teams in implementing AI within their local infrastructure – with ease and without compromising on data security and legal compliance.
Unlike SaaS LLMs, Deep Fellow runs entirely within your environment, adapts to your internal knowledge, and scales with your operations without exposing sensitive information or compromising auditability. You decide which data the system learns from, how it’s accessed, and where it runs.
Every interaction is traceable, every output verifiable, and every decision defensible. Because in domains where a data breach isn’t “if” but “when”, and where black-box AI is a non starter, trust isn’t a feature - it’s the foundation.
Why use DeepFellow ?
Private AI
under your control
Our models run entirely within your infrastructure, giving you full control over data, logic, and compliance. No data ever leaves your environment, and no third-party online LLM has access to your prompts, responses, or internal knowledge base.
Safe access to internal data without exposure
AI operates on your organization’s data through secure, server-side integrations. It accesses only what you allow it to, and nothing more – enabling powerful automation and decision support, without sacrificing data protection.
Marketplace-level capabilities - on your terms
DeepFellow integrates with leading MCPs and external tools, enabling secure use of market-standard models within your private context. Custom connectors ensure compatibility with your tech stack without exposing internal data.
Infrastructure for rapid implementation of E2E Encryption
Ready-to-use toolkit enabling total privacy of all communications and data sharing in apps. It supports dev teams in securing all types of data across platforms, both in new applications and already existing systems.
PrivMX works across environments, providing full security and control of data at all times - from the moment it's sent until it's decrypted by an authorized recipient. No third party can access it at any time, as it's based on Zero-Knowledge servers. With smart key management policy it allows for nuanced access control, optimising time-to-market and supporting teams in achieving legal compliance.
PrivMX for End-to-End Encrypted VR
The first complete E2EE framework for privacy in the metaverse
This toolkit allows devs to use encryption in streaming to protect all types of sensitive, biometric and environmental data.
It supports the VR community in creating privacy-friendly metaverse solutions that comply with legal regulations and protects data at all times.
Developed as a plugin within PrivMX toolkit, it's now adopted in Cortex2 - a EU-supported XR project facilitating remote collaboration.