VPS Requirements Estimator — Size the Server Your AI Team Needs

You've decided to self-host an AI team. Good call — your data stays on your server, and you pay a provider for compute instead of a per-seat SaaS bill. Then comes the question nobody prepped you for: how big a server do you actually need? Too small and the agents crash on out-of-memory errors mid-task. Too big and you're paying every month for RAM that sits idle. Most people guess, buy wrong, and either scramble to resize or quietly overspend forever.

The awkward part is that "run an AI office" doesn't map to an obvious spec. It's not one model on a GPU — it's five agents, a task board, a memory service and a control panel, all in Docker, sized by how many people use it and how hard they push it. That's exactly the gap the free VPS Requirements Estimator closes.

Why guessing the spec costs you either way

Server sizing has a nasty asymmetry. Guess too *low* and the failure is loud: agents get killed by the OOM reaper, tasks half-finish, and your first day self-hosting turns into a memory-pressure debugging session. Guess too *high* and the failure is silent — the office runs fine, and you never notice you're renting a 32 GB box to do 12 GB of work, month after month.

Neither is a knowledge problem you should have to solve by hand. The requirements are known; they just depend on a few things about how you'll use the office. The estimator encodes those rules so you get the answer before you spend a cent on the wrong plan.

What you actually get from it

You set three sliders and switches, and the output updates live:

• RAM, vCPU and disk, sized to your team. Move the team-size slider, pick a workload level, and the spec scales — a light-usage office of five lands near the 8 GB floor, a busy shop with more people climbs to 16 GB and up. Every number rounds to a real VPS tier, so it maps to a plan you can actually buy.

• A clear answer on the local helper model. One checkbox asks whether you'll run a bundled small model on the server to handle routine work for $0 in API tokens. Tick it and the recommendation adds the roughly 8 GB that model needs — so you size for it up front instead of hitting a wall later.

• Real monthly cost, not a vague "it depends." The spec maps to a price band anchored to actual 2026 VPS pricing (Hetzner CPX as the reference, DigitalOcean and Vultr similar or higher), so you see what your server will cost before you buy it.

• Providers and a shareable link. It lists popular hosts to buy from and gives you a share button, so the exact spec and price go straight to whoever approves the server — no re-typing, no screenshots.

The whole thing is rule-based and runs in your browser. The numbers come from the same minimums OfficeForge's installer checks on first run, so you're not sizing against a marketing figure — you're sizing against what the software actually needs.

Right-sized on the first try

The point of sizing before you buy is that you only do the setup once. Pick the box the estimator points to, install OfficeForge, and it just fits — no resize, no migration, no surprise OOM. If you want the reasoning behind the numbers — why 8 GB is the floor, what the local helper really costs in memory, when to jump to 16 or 32 GB — the companion guide walks through it: VPS requirements for a self-hosted AI team.

And if your needs grow, the estimator is the same thirty-second check next time. Bump the team size, re-run it, and you know exactly which tier to move to — sizing stays a decision you make with numbers, not a thing you rediscover the hard way.

Try it before you buy the server

Spend thirty seconds in the VPS Requirements Estimator: set your team size, choose a workload level, decide on the local helper, and read off the RAM, vCPU, disk and monthly cost. Buy that box, deploy OfficeForge on it, and start working — right-sized from day one, with no over- or under-buying to unwind later.