Entelligence AI Review (2026)

Entelligence AI Overview

Entelligence AI is an AI code review product with two defining characteristics, and they pull in opposite directions.

The first is pricing other vendors should copy. Entelligence bills in flat monthly bands rather than per seat: $750/month for up to 15 engineers with 300 reviews included, $2,500/month for 16 to 50 engineers with 1,000 reviews, and $1 per review beyond the allowance (verified 2026-10-19). It is also one of only three vendors in this entire category that publishes an enterprise rate card at all - the others being Snyk and Gitar. Twelve of the fifteen enterprise tiers we checked are quote-only, which is itself one of the more revealing facts about this market.

The second is that Entelligence publishes the Entelligence Code Review Benchmark 2026 and wins it. First on aggregate at 47.2% F1, first on Cal.com at 68.1% F1. We report that as a vendor benchmark, exactly as we report Greptile’s 82% self-score, DeepSource’s 84.51% F1, Qodo’s 60.1%, Propel’s 64%, Macroscope’s 48.31%, and CodeAnt’s 300K-PR benchmark that recommends CodeAnt. Every vendor that benchmarks itself in this market finishes first in its own benchmark. That consistency is the finding.

We are not going to sneer at it, though, because the benchmark contains something genuinely valuable that almost nothing else in this category publishes. More on that below.

Feature Deep Dive

Self-healing code review. On every tier, including Startup. Entelligence’s framing is that the reviewer does not only flag but proposes and iterates on fixes. The operational comparison point is Gitar, which commits a fix, runs CI, and commits only on green with automatic follow-up repair if its own fix breaks the build - and whose owner Sonar states plainly that a green build is evidence, not proof. That caveat applies to every self-fixing reviewer in this market.

Model Router. Enterprise only. Entelligence routes reviews across models rather than pinning one. This is a defensible architectural response to its own per-repository variance data: if quality swings this hard by codebase, routing per repository is a rational answer. It is also the single feature we would most want on the mid tier and cannot get there.

Knowledge Base and Agent Insights. Both Enterprise only. Agent Insights in particular is explicitly listed as unavailable on Startup and Scale, which thins the two published tiers out considerably.

Self-hosting and bring-your-own-key. Enterprise only. If self-hosting is a hard requirement and you would rather not enter an enterprise negotiation, Kodus is AGPLv3 and free to self-host at any team size and PR-Agent is MIT. See self-hosted AI code review tools for the deployment-level breakdown.

Platform coverage, unconfirmed. Entelligence’s pricing page does not state which Git platforms it supports, and we are not going to assume. GitHub and GitLab are the safe baseline for anything in this category, but confirm your forge directly if you are on GitHub Enterprise Server, Bitbucket Data Center or Azure DevOps. See AI code review on GitLab, Bitbucket and Azure DevOps for the tools where we could verify coverage.

Pricing and Plans

Band	Price	Team size	Included reviews	Overage
Startup	$750/month	Up to 15 engineers	300/month	$1 per review
Scale	$2,500/month	16 to 50 engineers	1,000/month	$1 per review
Enterprise	Custom	Custom	Not published	Not published

All figures verified at the Entelligence pricing page on 2026-10-19.

Why the model is good. A flat band with a published review allowance and a published overage rate is far easier to forecast than the alternatives. CodeRabbit charges per developer plus $0.25 per reviewed file in overage with linked-repository caps of 1, 5, 10 and 20 by tier. Greptile’s credits are per author and do not pool, and Apex-depth reviews cost 10 credits each. Qodo’s credit packs do not roll over. Macroscope has four usage modes spanning $0.025 to $0.20 per KB, an 8x spread inside one vendor, and re-reviews are billed every time. Against that field, one line item is a real product feature. See the AI code review price book for every vendor normalised.

Why the numbers still hurt. $750/month is the highest entry floor we have recorded in this category. A five-engineer team pays $150 per engineer per month. A fifteen-engineer team pays $50. And the band boundary is a cliff: hiring a sixteenth engineer takes the bill from $750 to $2,500, a 233% increase for one person. If you are sitting at 14 or 15 engineers and growing, model that before you sign.

Check the allowance against your throughput. 300 reviews a month across 15 engineers is 20 reviews per engineer per month. If your workflow re-reviews on every push rather than once per PR, you will clear that. At 600 reviews the Startup bill is $1,050, not $750. See what AI code review costs for team-level modelling.

How Good Is It, Honestly

The ranking is self-published and we discount it accordingly. Entelligence’s own benchmark places Entelligence first at 47.2% F1 aggregate and 68.1% F1 on Cal.com. The rest of the Cal.com table, reported as Entelligence reports it:

Tool	Cal.com F1, per Entelligence’s own benchmark
Entelligence	68.1%
OpenAI Codex	58.8%
Claude	52.2%
Cursor Bugbot	50.0%
Greptile	47.4%
CodeRabbit	46.0%
GitHub Copilot	37.0%
Graphite	0.0%

Treat the ordering as marketing. A 0.0% score for a shipping product is the kind of result that usually indicates a harness or configuration problem rather than a product that finds nothing, and a benchmark author has no incentive to chase that down. Note also that any Copilot evaluation run before September 2026 is invalidated by GitHub removing its 300-file and 20,000-line PR caps on 27 August 2026, and we do not know this benchmark’s run dates.

The part worth keeping is the variance. On Grafana, a Go codebase, Entelligence records perfect precision against only 33.3% recall. That is a real, specific, published measurement that review quality swings hard by language and repository, and it is close to the only per-repository data anyone in this market publishes. No vendor publishes per-language precision or recall for its own product, and SWE-PRBench, CR-Bench, CRBugBench and c-CRAB have zero language breakouts between them. Entelligence’s per-repo table, self-serving ranking and all, is one of the few pieces of evidence available on the question buyers most want answered.

The practical consequence for a buyer is the one Entelligence’s own data implies: any single aggregate F1 figure, from any vendor, is averaging over a spread wide enough to invert the ranking on your particular codebase. Trial on your repositories, in your language.

One figure that gets misattributed constantly. In Entelligence’s data Claude scores 43.3% recall against 42.3% precision. The separate and widely-quoted figure of roughly 51% recall and 23% precision for Claude Code comes from Augment’s re-run on a different dataset, not from Entelligence. The two are routinely conflated.

The standing caveat: no independent benchmark has scored Entelligence - it appears in none of Martian Code Review Bench, GitHub ReviewBench, SWE-PRBench, CR-Bench, CRBugBench or c-CRAB (checked 2026-10-19). And no party without a commercial stake has published a false-positive rate, precision figure or noise measurement for any shipping commercial AI code reviewer. See every AI code review benchmark compared for the full provenance map and our Noise Index methodology for the measurement we are running to close that gap.

Who Should Use Entelligence AI

A strong fit if: you are between roughly 10 and 50 engineers and your finance function wants one predictable monthly line item; you have been burned by credit-based billing that does not pool or does not roll over; you want a published overage rate rather than a surprise invoice; or you are an enterprise buyer who values seeing a rate card before the first sales call, which is rare enough in this category to be worth something.

Look elsewhere if: you are under about 10 engineers, where $750/month is above $75 per engineer and Kodus at $10, Sourcery at $12 or Korbit at $12 annual are all credible; you are sitting right at 15 engineers and growing, where the band cliff is a real cost; you need Model Router, Knowledge Base, Agent Insights or self-hosting without an Enterprise negotiation; or you need confirmed Bitbucket Data Center or Azure DevOps support, where CodeAnt and CodeRabbit both verify.

Entelligence AI vs Alternatives

	Entelligence	CodeRabbit	Greptile	Macroscope
Billing model	Flat monthly band	Per developer + per-file overage	Per seat + non-pooling credits	Pure usage, per KB reviewed
Entry paid price	$750/mo (up to 15 engineers)	$24/dev/mo annual	$30/seat/mo	$0.05/KB, $0.50 floor
Cost at 15 engineers	$750/mo	$360/mo	$450/mo	Usage-dependent
Included reviews	300/mo, then $1 each	Hourly limits 5 to 12 by tier	50 credits/seat, no pooling	None, pay per review
Enterprise rate card published	Yes	No	No	Not applicable
Free tier	None published, signup trial only	Free on public repos	Free for 1 active dev	$100 new-workspace credit
Self-hosting	Enterprise only	500+ seats only	Not published	No
Own benchmark, own first place	Yes, 47.2% F1 aggregate	No self-benchmark	Yes, 82% self-score	Yes, 48.31%
Independent benchmark score	None	Martian, 51.2% F1	Augment re-run, 45% F	None

All cells verified 2026-10-19 except the Martian and Augment figures, which are from the published benchmarks.

The honest read of that table: Entelligence is the most expensive option at 15 engineers and the most predictable one. CodeRabbit at $360/month for the same team is less than half the price, and it is the only tool in the comparison with a score on a leaderboard published by someone who does not sell a reviewer - Martian sells model routing. Greptile’s 82-vs-45 gap is instructive and more nuanced than it looks: Augment did not reuse Greptile’s answer key, stating that it expanded and corrected the golden comments by reviewing each PR manually, so part of that gap is a different answer key rather than pure self-dealing.

Against Macroscope, the contrast is philosophical. Macroscope is pure usage billing with a published average review cost of $0.95 and no seat fees; Entelligence is a flat band with a review ceiling. If your PR volume is spiky, usage billing is cheaper. If your finance function hates variance, the band wins.

Pros and Cons Deep Dive

The pricing transparency is the best thing here, and we would like more of it. A published enterprise rate card puts Entelligence in a group of three out of fifteen. A published included-review allowance and a published $1 overage rate put it ahead of most of the field on forecastability. In a market where 12 of 15 enterprise tiers are quote-only, that is worth saying clearly.

The flat band genuinely solves a real problem. Per-seat-plus-credits models in this category are a mess: Greptile’s credits do not pool across authors, Qodo’s do not roll over, CodeRabbit charges $0.25 per reviewed file in overage and caps Essentials at a single linked repository, and Macroscope’s four modes span an 8x cost range. One line item is a feature.

The entry floor is the hardest objection. $750/month is the highest we have recorded. Below about 10 engineers the per-head maths is bad and gets worse the smaller you are.

The band cliff is the second hardest. $750 to $2,500 on the sixteenth hire. That is a 233% step for one person, and it lands exactly at the size where fast-growing startups live.

Enterprise gating thins the published tiers. Model Router, Knowledge Base, Agent Insights and self-hosting are all above the rate card. The two tiers you can actually price are the two with the least in them.

The benchmark is self-winning, and we discount it fully. Same treatment as Greptile, DeepSource, Qodo, CodeAnt, Propel and Macroscope. No exceptions, no favourites.

The variance data is a real contribution and we will keep citing it. Perfect precision at 33.3% recall on a Go codebase is the kind of concrete, inconvenient number that advances the conversation. Publishing a result that undercuts your own aggregate score is a point in Entelligence’s favour, and we would rather say so than score cheap points.

For the shortlist in context, see the best AI code review tools, the best AI PR review tools, and how to evaluate an AI code reviewer. If you are buying at enterprise scale, AI code review for enterprise covers what the rate cards do not.