The model is free.
The architecture
is the moat.
AI is now open source. Anyone can call a frontier model. The real work — the part nobody can copy from a tutorial — is architecting a sovereign mesh that runs your business. NAVADA Edge is a working blueprint: six nodes, twenty-nine containers, one operator. Each node a department. Each container a function. All orchestrated by AI agents. Use it as a textbook, or hire the developer who built it.
Command Workstation
A frontier model is a commodity now.
What you do around it is everything.
API access · pennies per million tokens
Free.
Open weights run on your hardware. Frontier APIs cost pennies. The intelligence layer is no longer the constraint.
The moat.
Stitching the model, your data, your tools, and your business into one mesh — that's the part nobody can copy from a tutorial.
What you pay for.
A developer who has built it before. Knows the failure modes. Brings you to production in weeks, not years.
What's actually running, right now.
Operator · 01
Twelve people for twelve jobs
was the old way.
Run-rate · ~£70/month
One human per business function.
A marketer, an SDR, an account manager, a bookkeeper, a community manager, a researcher, a head of ops. Each one a salary, a slack channel, a calendar, a turnover risk. And still, the work piles up.
- × 8 to 12 hires before you ship anything
- × Six-figure burn before product-market fit
- × Coordination overhead grows quadratically
- × Knowledge leaves when people leave
- × Vendor SaaS bills compound monthly
- × You manage humans instead of building
One node per business function.
A marketing node. A sales node. An ops node. A knowledge node. A research node. A delivery node. Each one runs containers. Each container holds an AI agent that knows that part of the business. You operate the mesh.
- + One operator running an entire business
- + ~£70/month all-in for the reference build
- + Knowledge lives in the mesh, not in someone's head
- + Add capacity by deploying a container, not hiring
- + Single-tenant, sovereign, no shared blast radius
- + You build instead of managing
Six nodes. Six departments. One operator.
Build this stack · 4 to 8 weeks
Picture a one-person business as if it had departments — marketing, sales, ops, knowledge, R&D, intelligence. In a traditional company, each is a team. In an Edge Network, each is a node running containers and AI agents. Here is the working reference build.
Command Node
Customer-facing Node
Memory Node
Workflow Node
Edge Node
Data Node
Docker-first. Cloudflare top.
Tailscale + Nginx always.
Principle · Add capability, never change architecture
Seven tiers, all built from open standards and battle-tested open-source software. No proprietary platforms. No vendor lock-in. You can read every line.
What this mesh can do
that your stack probably can't.
Each one production-tested
No open ports. Anywhere.
Every node sits behind a private Tailscale WireGuard mesh. Nothing inbound on the public internet except what passes through Cloudflare Zero Trust — identity-aware, rate-limited, WAF-protected, fully audited. Secrets live in a managed vault. Container-to-container traffic is encrypted by default. No firewall hole has ever been opened on this network.
- · Tailscale ACL governs node-to-node access
- · Cloudflare Access on every public surface
- · Tamper-evident audit log on every action
- · Tiered API keys with revocation in seconds
Capacity ships as a container.
New capability is a new container, not a new platform. New region is a new node joined to the mesh. New customer tier is a new API key. The architecture is designed to grow horizontally for years without a rewrite. The reference network has gone from 4 to 29 containers without changing the underlying model.
- · Horizontal — add nodes for capacity or geography
- · Vertical — summon GPU on-demand, release on idle
- · Multi-tenant when needed, single-tenant by default
- · Same blueprint scales from solo founder to mid-market
Operate the business from your phone.
A Telegram chat replaces the on-call dashboard. The resident AI agent and an SSH-capable bot give you remote command of every node — health checks, deploys, log tails, container restarts, file edits, even ad-hoc shell commands. An incident at 2 AM is two taps on a phone, not a laptop boot and a VPN dance.
- · Chief-of-staff agent for everyday ops questions
- · Ops-tools agent for protected admin actions
- · Incident alerts pushed in the same channel
- · Same model works for Slack, Discord, or your own surface
The mesh extends to your hardware.
A node does not have to be a server. The reference network includes a hexapod robotics rig running ROS — joined to the same private mesh, controllable from the same dashboard, observable from the same Grafana. The same architecture works for any robot, sensor, vehicle, or piece of equipment that needs local compute and a path back to the network.
- · ROS 2 substrate for autonomous control loops
- · Computer vision and telemetry pipelines
- · Mesh-joined for remote operation and learning sync
- · Works for industrial, agricultural, or research deployments
A full-stack developer who has
shipped this — not just talked about it.
Based · United Kingdom
I am a full-stack developer with 17+ years of enterprise infrastructure experience. The reference network on this site — six nodes, twenty-nine containers, a private mesh, a production AI agent stack — was built and is operated by me, alone. No platform team. No SREs. No DevOps department.
I work end-to-end: front-end, back-end, infrastructure, agents, data, observability, security. I have spent the last two years using AI as a daily collaborator to ship business outcomes — not demos. The expertise I sell is the assembly of those pieces into something that actually runs in production for years.
If you are a founder, an operator, or a small team trying to figure out how to use AI to do the work of a department — I am the person you want in the room.
- · Full-stack engineering — TS / Node / Python / Go
- · Distributed systems — Docker, Kubernetes, mesh VPN
- · AI integration — Anthropic, OpenAI, Bedrock, open-weights
- · Agent design — MCP, tool use, memory, evaluation
- · Data engineering — PostgreSQL, Snowflake, vector stores
- · Cloud — AWS, Azure, Cloudflare, Oracle, GCP
- · Observability + security — Zero Trust, audit, hardening
- · Business — translating C-suite ask into shipped code
Tools you can use right now.
NAVADA Edge CLI
Sixty-nine commands, sixteen built-in tools, a skills framework, three-tier memory, five AI providers. The command-line for the entire network. Free to install, free to use.
EXPLORE THE CLI →NAVADA Edge SDK
Programmatic access to the automation queue, edge runtime, and agent workflows. JavaScript and TypeScript first. Use it inside your own product to lean on the mesh instead of rebuilding it.
EXPLORE THE SDK →Edge Portal
The customer-facing dashboard for the network. API key management, usage analytics, agent configuration. Cloudflare Zero Trust authentication on every request.
OPEN THE PORTAL →Two tracks. You choose.
All prices starting from. Open to negotiation based on scope, stage, and longer engagements. Free 30-minute discovery call comes first. Final scope confirmed in writing before any commitment.
Build With Me.
We take it end-to-end. Architecture, code, deploys, training. Fast and zero-rework, premium price.
- A1 · Architecture from £1,250
- A2 · Implementation from £7,500
- A3 · Managed from £2,250/mo
Teach Me.
You do the work. We bring the blueprint, playbooks, and debugging hours you skip. A fraction of the cost.
- B1 · Workshop from £750
- B2 · Mentored Build from £2,000
- B3 · Office Hours from £300/mo
"Every founder I talk to wants to use AI. Most are paying a vendor a hundred thousand a year for the right to. The Edge Network is what happens when one developer refuses that trade and shows you how to refuse it too."
LEE AKPAREVA · FULL-STACK DEVELOPER · OPERATOR · NAVADA
A 30-minute call. No deck.
Tell me what your business does and where you wish AI was already doing the work. We will tell you whether a mesh fits, what it would cost, and roughly how long. Honest answers either way.