Scrunch AI alternatives and competitors

The common mistake is treating scrunch ai competitors as a feature hunt. You open the Scrunch AI pricing page, see one priced plan and a custom tier, then arrange a call before you know whether the tool fits. That delay can push the decision past the budget meeting: the call gets booked, the quote arrives afterwards, and you are comparing from memory instead of against another price.

This post is for the person searching scrunch ai pricing who wants a usable alternative now. Scrunch’s pricing page says its Core plan is for teams to “evaluate Scrunch, establish AI visibility benchmarks, and prove impact before scaling”, while higher needs are described with custom prompts, workspaces and a dedicated account team. That is a sensible enterprise sales path. It is less useful when you are a small team trying to make a buying decision this afternoon.

Scrunch prices Core, then moves to a quote

The entry plan on Scrunch’s pricing page, Core, is $250 a month and lists “125 unique prompts”, “5 site audits / month”, “1 brand workspace” and “5 user licenses”. The page does not say whether the $250 is billed monthly or yearly, and it offers a “Start 7-day free trial” option. Those details were checked on 2 Oct 2026.

The higher tier is described as being for organisations that need expanded model coverage, advanced features, API access and dedicated support. It lists a custom number of prompts, custom brand workspaces and a dedicated account team. Its FAQ says annual discounts are offered to Enterprise clients, with annual agreements paid upfront getting a discount equal to two months free, but it gives no Enterprise figure.

This is a buying model, not evidence of intent. If you need procurement support and a negotiated package, it may suit you. If you need a number for anything beyond Core, it creates friction at that step.

Alternatives need a public price

A useful alternative should show what it costs and what the limits are. It should also help you answer the practical question behind the purchase: which products get named, which pages get cited and what should you change next.

For example, ask a product whether it can show why a buyer question produced a named competitor but no citation to your site. If the answer only gives you a visibility score, it leaves out the fact you need to fix. A report is useful when it connects the question to the answer, the cited page or the missing fact.

CiteGraph publishes its limits. Starter is $29 a month for 2 projects, 10 questions each, 3 runs per question on 4 engines, 6 tracked rivals and 30 written pages a month. Growth is $69 a month for 3 projects, 10 questions each on 4 engines, 10 tracked rivals and 60 written pages a month.

ChatGPT Only is $19 a month for 1 project and 20 questions, asked on ChatGPT only. Weekly scans ask each question 3 times on every plan; a scan you start on Growth asks it 5 times. Every plan is paid from the day it starts and can be cancelled at any time.

Being named is not being cited

Our weekly leaderboard gives a rough view of the category, not a buying verdict. It uses 80 answers to 10 buyer questions across 4 engines. In that sample, Otterly is named in 60% of answers, Peec AI in 53%, Profound in 48%, Semrush in 33% and Ahrefs in 18%.

Scrunch is named in 10% of answers, with an interval of 5 to 19. Its own site is cited in 4%. The page cited most for Scrunch in this sample is a Profound integrations page, not Scrunch’s own site. Being named and owning the cited source are different outcomes.

The rest of the sample includes AthenaHQ at 14%, HubSpot AEO Grader at 13%, Rankscale at 9% and AirOps at 9%. These figures describe this set of questions and engines. They do not predict your category, your buyers or your next answer.

The interval is wide because the sample is small. We measure samples, print margins and do not know what we have not measured.

Public limits show the workload

A public price lets you calculate whether a tool can cover the work you actually have.

CiteGraph publishes fixed monthly prices of $19, $29 and $69. Its plans show the number of projects, questions, runs, engines, tracked rivals and written pages before you subscribe. The pricing page says, “Every plan, every limit, on one page.”

The same page says, “No form and no ‘contact us’ for the numbers.” It also lists monthly billing, cancellation at any time and a 120-day guarantee.

The page still carries evidence

A monitoring tool cannot repair a vague product page by itself. If the page never states who the product serves, what it replaces, how it differs and what it costs, an answer engine has less material to use. A report may show that gap. Your page still needs to close it.

Imagine a homepage that only says, “We help brands win in the age of AI.”

Now compare it with this illustrative rewrite: “This AI visibility tracker shows marketing teams which buyer questions name their product, which pages they cite and what the plan costs.”

The second sentence gives an answer engine more usable material: a product category, a buyer, an outcome and a buying detail. It still does not guarantee a citation. It reduces avoidable ambiguity.

If you want a quick starting point, run the free AI readiness check. It needs no account, runs 15 checks and shows the fix for each. This is a diagnostic, not a substitute for reading the pages your buyers and competitors have published.

You can test fit in an hour

You do not need a long procurement exercise to reject a poor fit. Use a small, repeatable diagnostic before you compare every feature.

1. Write down the buyer questions you need the tool to monitor, using the wording customers already use.
2. Check whether the product shows a fixed price, project limits, question limits and scan or run limits in public.
3. Run the same questions through the trial, scan option or free checker available to you.
4. Save the named products, cited pages and missing facts, then decide whether the output gives you a page change you can assign.

That is the under-an-hour exercise. Publishing the page change and checking the questions again is a separate, later exercise, because the systems need time to recrawl and answer again.

Keep the test narrow. You are checking whether the workflow produces decisions, not awarding a trophy for the fullest dashboard.

CiteGraph can also run as an MCP server. Its MCP documentation says Claude, Cursor or VS Code can read a scan and apply readiness fixes in a repository. That may suit a team that wants the finding to move directly into an engineering or content workflow.

The useful comparison is less “which tool has the longest list” and more “which tool gets a finding into the hands of the person who can fix it”. Public pricing helps with the first part of that decision. A small test handles the second.

Choose the buying model first

Scrunch is positioned for a conversation-led enterprise purchase. Its page offers a trial and shows some starting limits, then moves larger requirements towards custom prompts, custom workspaces, expanded coverage, API access and dedicated support. Beyond Core’s $250 a month, the price question is part of the sales process.

CiteGraph suits a buyer who wants a visible monthly number and a small-team starting point. Scrunch may suit an organisation that wants a tailored package and account support. The real split is between buying models, not a contest over feature labels.

If you want to investigate the wider field first, the weekly research on who owns AI answers gives you a broader view, while the leaderboard shows this sample and its limits.

For a buyer comparing Scrunch AI competitors, the practical alternative is a tool with public limits, a testable workflow and a price you can see before the call.