Self-Hosted AI Code Review Under 500 Seats: What Your Options Actually Are

There is a specific and surprisingly common place to get stuck when shopping for AI code review. Your security team has a hard requirement that source code does not leave your infrastructure. You go looking for a self-hosted option. And then you discover that the self-hosted tier of the tool you were evaluating starts at 500 seats.

You have forty engineers. Or ninety. Or two hundred. The requirement is real, the budget is not imaginary, and yet the market appears to have decided that self-hosting is something only enterprises with a four-figure headcount are allowed to want.

This is a guide to what your options actually are in that situation — including the honest limitations of each one, and where PURA fits.

Why the 500-seat wall exists

It is worth understanding the commercial logic, because it tells you which vendors will and will not move.

CodeRabbit, the most widely evaluated tool in this category, offers self-hosted deployment only on its Enterprise plan, which carries a minimum of roughly 500 seats and list pricing starting around $15,000 per month. On top of the subscription, teams running it in their own cloud report additional infrastructure costs in the hundreds to several thousands of dollars per month depending on scale. We break down the full plan structure in our guide to what CodeRabbit actually costs per developer.

That minimum is not arbitrary. A self-hosted deployment is a different product from a multi-tenant SaaS one: it needs installation support, an upgrade path the vendor does not control, debugging in an environment the vendor cannot see, and a security review process per customer. The vendor has to amortise that cost over something, and headcount is the lever available. A 40-person team buying self-hosted consumes nearly as much vendor attention as a 2,000-person one while paying a fraction as much.

So the wall is structural rather than technical, which means the way past it is usually a vendor whose architecture makes self-hosting cheap to support — not a negotiation.

Option 1: open-source, self-hosted, bring your own keys

The floor of the market. Tools like PR-Agent are open source, run on your own infrastructure, and call an LLM using API keys you supply. There is no seat minimum because there are no seats.

What you get: complete control of the deployment, no per-user pricing, and code that never touches a vendor's servers. For a team with strong platform engineering and a tolerance for maintaining another internal service, this is a legitimate answer, and we have written about the category in more depth in open-source AI code review.

What you are actually signing up for: your code still goes to an LLM provider, unless you are also hosting the model. This is the detail that trips up teams most often — “self-hosted” and “your code never leaves your network” are not the same claim. If your compliance requirement is the second one, an open-source tool calling a hosted API does not satisfy it any more than SaaS does. It changes who holds the contract, not where the data goes.

You are also taking on the operational load: upgrades, prompt and model tuning, rate-limit handling, and someone owning it when it breaks during a release. Teams routinely underestimate this, and the honest version of the build-vs-buy calculation is in our build vs buy analysis.

Option 2: BYOK on a managed platform

A middle path that many teams under 500 seats end up preferring: the review platform is managed, but the model calls use your own provider credentials, against your own contract, under your own data-retention terms.

This solves a narrower problem than full self-hosting, and it is worth being clear about which one. It gives you control of the model relationship — which provider, which model, what retention policy, whose enterprise agreement governs the inference. It does not give you control of where the review platform runs. If your actual requirement is about the LLM provider rather than about network boundaries, bring-your-own-key AI code review is very likely the cheapest thing that satisfies it, and it has no seat minimum.

Worth checking before you go down this path: read your compliance requirement literally. A surprising share of “we need self-hosted” requirements turn out, on inspection, to be “we need a signed DPA and no training on our data” — which BYOK handles without any infrastructure work at all.

Option 3: single-tenant or self-hosted without the headcount floor

The third option is a vendor that will deploy into your environment regardless of how many engineers you have. This is what PURA does: the platform runs in your own AWS, GCP, Azure, Hetzner, DigitalOcean, or on-premise environment, and there is no 500-seat gate in front of it. Our broader guide to self-hosted AI code review covers the deployment shapes in detail.

The reason this is possible is architectural rather than generous: a platform designed from the start to be installed elsewhere costs far less to support in someone else's cloud than one that grew up as a multi-tenant SaaS and had self-hosting retrofitted onto it. The seat minimum on retrofitted products is paying for that retrofit.

The trade-off you should expect, from any vendor: self-hosted means you own the upgrade cadence and the infrastructure bill, and you are the one who notices first when something is wrong. It is genuinely more work than SaaS. It is worth it when the requirement is real, and it is overhead you are buying for no reason when it is not.

A short decision path

• Requirement is “no training on our code”. Almost every vendor contractually offers this now. You probably do not need self-hosting at all.
• Requirement is “our own LLM contract and retention terms”. BYOK on a managed platform. Cheapest, fastest, no infrastructure.
• Requirement is “code does not leave our network, including to the model”. You need true self-hosting with a model you also control. This is the strictest case and the one where the 500-seat wall actually bites.
• Requirement is “a specific regulator or customer audit”. Get the exact wording before choosing. The control that satisfies an auditor is frequently an audit trail rather than a deployment topology.

The thing to do first

Before comparing vendors, write down the requirement in one sentence and identify who owns it. Roughly half the teams that arrive at self-hosting as a conclusion have never had that sentence written down, and are solving a stricter problem than the one they actually have — at considerable cost in both money and engineering time.

If the requirement survives that test and you are under 500 seats, talk to us about a self-hosted deployment. There is no headcount floor, and the conversation starts with your compliance constraint rather than your org chart.