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Zylon

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About

Zylon is a self-contained, on-premise AI platform designed for enterprises that prioritizes data privacy and security. It runs entirely within the organization's infrastructure, eliminating external dependencies and ensuring complete control over sensitive data. Zylon offers features for collaboration, customization, and streamlined deployment, making it suitable for various industries. Built on the foundation of PrivateGPT, it provides a secure, scalable, and efficient platform for deploying and managing AI models and services. Zylon's collaborative workspace empowers teams to boost productivity, generate documents, and streamline projects while maintaining data privacy. It also provides enterprise-grade features like role-based access controls, advanced analytics, and robust history tracking.

Platform
Web
Task
private ai

Features

security

advanced analytics

collaborative workspace

scalability

role-based access controls

easy deployment

fully on-premise

robust history tracking with audit logs

FAQs

What makes Zylon the only Private AI solution?

Zylon runs on-premise, keeping data private. It runs on curated LLMs served from within your infrastructure, ensuring that your data is never sent over the internet in leaks or for training purposes. Zylon is an on-premise alternative to AI tools like ChatGPT that runs on your Virtual Private Cloud (AWS, Azure, GCP...) or local data center (even air-gapped) behind your firewall. This empowers our customers to leverage Large Language Models (LLMs) confidently, even when working with sensitive and proprietary information under heavy regulations. Zylon leverages the technology we created for PrivateGPT, the worldwide reference open-source project for Privacy in GenAI that proved feasible to run a fully local execution of a ChatGPT-like experience without Internet connection.

What are the advantages of an On-Premise system versus a SaaS one?

Unlike other AI software that requires sending sensitive data over the internet, Zylon runs on-premise, keeping data private and usable even where ChatGPT-like tools are banned. On-premise and private cloud deployments allow data-sensitive companies and those in regulated industries to adopt AI.

How is Zylon different to PrivateGPT?

PrivateGPT provides an API containing all the building blocks required to build private, context-aware AI applications. Since we launched it in May 2023, the project has created a community of 54k+ people on GitHub and 5k+ contributors on Discord, but the project is designed to be used by developers, hence it’s not an end-to-end product. Zylon has been built on top of PrivateGPT, complying with enterprise-grade security standards, to provide a versatile, end-to-end solution for data-sensitive organizations wanting to incorporate the power of AI in a fully private way.

What kind of data does Zylon work with?

Zylon lets you connect to your standard data sources, upload files and create new content within the tool. Any piece of data connected to Zylon remains fully in your system.

Can I try it out before making a commitment?

Yes, we'd love to learn more about your use case and help you test the right solution for it: from our Sandbox environment to setting up a pilot project.

How can I integrate Zylon into my company?

Zylon can be seamlessly integrated into most companies, from private clouds to data centers. Our solution architects will work directly with your IT team to finalize the process in a matter of days.

Job Opportunities

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Zylon

Platform Engineer

Zylon is a private, on-premise AI platform for enterprises, ensuring data sovereignty and control. It offers collaboration tools, easy deployment, and robust security features.

engineeringremotefull-time

Benefits:

  • Impactful Work

  • Collaborative Culture

  • Growth Opportunities

  • Flexibility

Experience Requirements:

  • 5+ years in platform engineering, SRE, SysOps, DevOps, or related roles, ideally within startups or AI-focused organizations

Other Requirements:

  • Strong programming skills (Python, Go, Bash, or similar)

  • Proficiency in containerization and orchestration tools (Docker, Kubernetes)

  • Proven experience with cloud platforms (AWS, GCP, Azure)

  • Deep understanding of infrastructure-as-code tools (Terraform, Pulumi, CloudFormation)

  • experience with bare metal deployments, high availability, scalability, and security best practices

  • Solid understanding of networking, firewalls, load balancers, and DNS management

  • Experience with tools like Prometheus, Grafana, Datadog, or similar

  • Excellent analytical and troubleshooting skills, with a proactive mindset

  • Strong interpersonal and communication skills to collaborate across teams and with clients

Responsibilities:

  • Platform Development & Maintenance

  • Infrastructure as Code

  • Monitoring & Observability

  • Cloud & Containerization

  • Collaboration with software and AI engineers, as well as product teams to ensure smooth deployment and operation of AI models and applications

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