Building a networking startup once required a large engineering team and years of work. A new company is betting that AI can compress that timeline dramatically, and it has raised venture funding to prove the point.

doxx.net launched this week with a platform it calls Agentic Defined Networking. The service lets users and their AI agents build private networks, and the startup announced a $38 million Series A round led by Andreessen Horowitz, with participation from Animo Ventures and Focal.vc.

The company was founded by Barrett Lyon, a serial entrepreneur who has built and sold multiple networking vendors over the past two decades. His previous companies include Prolexic, acquired by Akamai; defense.net, acquired by F5 Networks; and netography, acquired by Vectra AI. That track record gives the new venture a founder with deep experience in security, traffic management, and network infrastructure.

Key facts at a glance

• doxx.net has launched an Agentic Defined Networking platform for private networks built by users and AI agents.
• The company raised a $38 million Series A led by Andreessen Horowitz, with Animo Ventures and Focal.vc participating.
• The platform combines custom VPN transports, an encrypted global mesh, a separate control plane, its own DNS root, and a certificate authority.
• The network spans 31 locations worldwide and is managed by AI, according to founder Barrett Lyon.
• Administrators can issue read-only or admin tokens to agents, expire or revoke those tokens, and cut an agent’s gateway access.

The roots of doxx.net trace back to Darkflare, a hobby project Lyon built as a TCP tunnel over Cloudflare. The goal was to tunnel through public networks in a way that helped avoid detection and potential censorship. The response to that project led Lyon to consider a larger idea: a VPN that cannot be stopped and is autonomously managed by AI.

‘The hobby turned into an obsession, and the obsession turned into a business,’ Lyon said.

How the Agentic Defined Network works

The platform is not a single product but a combination of custom VPN transports, a company-run mesh, and a separate control plane. Each layer is designed to give users more control while allowing AI agents to automate configuration and operations.

Covert transports

The doxx.net client supports WireGuard and custom transports for VPN traffic over WebSocket, Session Initiation Protocol, ping, QUIC, Cloudflare, and HTTPS. These transports are designed to get through firewalls, which can be important for users who need connectivity across restrictive networks. Rather than relying on one protocol, the platform offers multiple paths for traffic, giving operators flexibility when a particular transport is blocked or degraded.

Mesh networking

The mesh connects every site to every site with encryption. It runs over IPv4 and IPv6 and is orchestrated through an application programming interface. That design allows the network to be managed programmatically, which is essential for AI agents that need to create links, change routes, or add services without waiting for manual intervention.

Separate control plane

Lyon said the client app is a device, not a control plane. Routing, port forwarding, and firewall rules are managed in a separate portal. Keeping control and data functions separate can simplify administration and reduce the risk that a compromised device can change network-wide policies. It also gives administrators a central place to review and govern what agents and users are allowed to do.

Addressing without NAT

Devices on the mesh are not behind network address translation or carrier-grade NAT, according to Lyon. That allows peer-to-peer applications to work more directly. In many corporate and consumer networks, NAT can complicate peer-to-peer traffic, voice, video, and file transfer. A mesh that assigns routable addresses can make those applications easier to deploy and operate.

DNS, certificates, and BGP

The company runs its own Domain Name System root with 196 domains and its own certificate authority. Lyon said the team wrote its own Border Gateway Protocol daemon and runs internal BGP across the mesh. Running internal DNS and certificate services gives the platform control over identity and naming inside the network. The internal BGP daemon helps the mesh route traffic between sites and services without depending entirely on external routing infrastructure.

Identity and discovery

The address book holds no phone numbers, email addresses, or names. Users exchange cryptographic keys and assign an alias to each contact. A directory service seeds a new device with the data needed to find its contacts, and after that initial call, devices sync with each other. This approach emphasizes cryptographic identity over personal identifiers, which fits the company’s privacy-oriented design.

How AI runs the network

The need for AI to run the network is pragmatic. Lyon said he turned to AI because he could not manage the network by himself. The platform spans 31 locations around the world, with an internal mesh connecting them. Managing that scale manually would require a large operations team, so the company built automation into the core of the service.

‘The whole thing is run completely by AI, so behind the scenes, I mean, it’s a network with 31 locations around the world, and internally there’s a mesh network, and I can’t, as a human being, manage all of this by myself,’ Lyon said.

Before building, the team modeled every site in a virtual environment, down to the wire and the optic. An infrastructure management system running the company’s own AI on its own hardware then ordered the installation. It orchestrated shipping and delivery through data center APIs, while human technicians performed the remote smart hands installations. That combination of AI planning and human physical work shows how the company is using automation not just for software configuration but for the buildout of physical infrastructure.

What agents can do on the network

The company also built tools for agents to work with users and with the network. An agent gateway gives an AI agent an identity in the doxx.net chat app. The user pastes a credential into the agent, the agent obtains its certificate, and it appears in the user’s chat. Users can create group chats with several agents. In one example, Lyon said one agent runs BGP while others handle different tasks.

The API is self-teaching. An agent given a configuration URL can learn how to build networks without further instructions. It then asks what the user wants to do, such as link an office to a house or give a Linux box a private IP address. Agents can also create their own domains and host names, sign certificates, and run web servers and applications inside the network.

Administrators issue read-only or admin tokens for each agent. Tokens can expire or be revoked. An administrator can also cut an agent’s gateway access or delete the agent in the app. That permission model is important because agents may act autonomously, and organizations need a way to limit and audit what each agent can do.

‘You don’t just give them your account credentials to the master account,’ Lyon said.

From hacker handle to network platform

The term doxxing usually refers to publishing someone’s private information, but that is the opposite of what doxx.net is designed to do. Lyon registered the domain more than 30 years ago because it was his hacker name at the time. The name now carries a different meaning for the company.

‘So, I’m just reclaiming the word, and it is kind of funny that we’re doing the exact opposite of what doxing is. And, I don’t know, it just seems fitting for me,’ he said.

What comes next

Looking forward, the plan is to build out more enterprise offerings and release some code as open source. The company’s broader thesis is that AI is not just a tool for managing networks but a tool for building the technology itself. That distinction matters: AI can help configure routes and policies, but it can also help design, deploy, and maintain the underlying systems.

‘You can have a vision of where it’s going to go, and then that vision hits a wall when you hit, you know, your own personal limitations,’ Lyon said. ‘The AI just takes it well beyond, running this with an agentic partner, so to speak, turns this into fire.’

Source: Network World News