Originally published on the Dromeas blog.
Every AI code review vendor's homepage says the same three words: "AI-powered code review." That's not useful information anymore — of course it's AI-powered, it's 2026. The questions that actually separate these tools are more specific, and most comparison content in this category is either a vendor's own battlecard or a listicle nobody fact-checked. Here are six questions worth asking directly, in a demo or a trial, before you sign anything.
1. Does it review one point in the pipeline, or every point?
A bot on the PR is the default shape of this category. Ask what happens to a commit that lands directly on trunk, or a change that ships six weeks after the PR that introduced the underlying risk. If the answer is "we don't look there," that's not disqualifying on its own — but it's a gap you're accepting, and you should know you're accepting it. In our own measurements of 100,000+ PRs across 500+ open-source repos, a meaningful share of changes never went through a PR at all — so "we review PRs" and "we review your code" are materially different claims. The data on that is public.
2. Is a finding one model's opinion, or several checking each other?
Single-model review inherits that one model's blind spots. Ask whether the vendor runs more than one model against the same diff, and whether you can see where they disagreed. "We use GPT-5" is not the same claim as "three models reviewed this independently and here's where they split." The disagreement record is the useful part: a tool that hides it is asking you to trust a single point of failure with a friendly UI. (We wrote up how we built our own multi-model council if you want to see what the transparent version looks like.)
3. What happens after "no findings"?
A clean PR review says nothing about test coverage, stale docs, or missing observability on the code that just shipped. Ask whether the tool's job ends at the diff, or whether it's also checking the five other things that determine whether a release is actually safe. "No findings" should be the start of a release conversation, not the end of a review.
4. Who checks compliance, and how?
If you're regulated — SOC 2, HIPAA, PCI, GDPR — ask directly whether compliance is a first-class check or a slide in the sales deck. Most tools in this category are quality- or security-first and don't cover this at all; that's a fair trade-off if you don't need it, and a real gap if you do. The tell: ask to see a compliance finding in the demo, not a slide about one.
5. Per-seat, or usage-based?
Per-seat pricing was built for a world where humans opened PRs. As agents start committing more often than people do, seat count stops tracking the thing that's actually driving cost or risk. Ask how pricing behaves as commit volume rises independent of headcount — and whether you'll be penalized for the agent-heavy workflow the same vendor's marketing encourages.
6. Can your coding agent actually talk to it?
MCP support is now table stakes to claim, but "we have an MCP server" and "your agent can ask this tool for a verdict and act on it" are different claims. Ask what a coding agent can actually do through the integration — read-only context, or a working verify-and-fix loop. A quick test: can your agent submit its uncommitted diff for review and receive a verdict it can act on, without you leaving the terminal?
Ask everyone — including us
None of these questions require you to already know what you're comparing against. Ask them of any vendor, including us — the answers are the actual differentiator, not the marketing copy above them.
If you want the specific answers for the vendors you're already evaluating, the comparison hub has the full feature-by-feature breakdowns — CodeRabbit, SonarQube, Copilot, Snyk and more, each with sources and a last-verified date.
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