DeepSmith vs Cited.so: Citation Tracking vs Earning Citations End to End

The deepsmith vs cited.so decision is not really a choice between two versions of the same tool. It is a choice between two operating models for AI search. Cited.so is a done-for-you content service that writes and publishes articles on a customer's own site and frames that work as the route to Google rankings and ChatGPT recommendations. DeepSmith is a self-serve platform that tracks where a brand is and is not cited across five AI engines, surfaces the gaps, and produces the content to close them inside the same workspace. The two products approach the same job, earning visibility in AI answers, from opposite ends: one hands the work to a vendor and reports outcomes, the other gives the team the data and the production engine and expects the team to run it.

For a marketing lead evaluating AI citation tracking software, the practical question is whether visibility should be measured and acted on in-house, or delegated to a managed service that treats the underlying data as its own concern. The sections below compare the two on what each surfaces, what each produces, and which reader situation each fits. Facts about Cited.so are drawn from its public site; where the public product does not expose a capability, that absence is noted rather than assumed away.

DeepSmith vs Cited.so at a glance

The two products differ on almost every structural dimension, from primary buyer to whether the customer ever sees citation data. The table summarizes the head-to-head before the sections examine each dimension in detail.

What Cited.so is, and what it is not

Cited.so presents itself as a managed service rather than a piece of software the customer operates. The homepage headline reads "We Rank Your Business on Google and ChatGPT," and the pricing contrast is stated plainly: agencies charge roughly $3,000 per month, Cited.so charges $99. The audience is named repeatedly and consistently as local business owners, with the site citing more than 500 local businesses across the United States and featuring customers such as a gym management platform, a team scheduling tool, a fitness studio product, and a roofing contractor. This is a product built for owners who want results without running a content function.

The product model is done-for-you, not a dashboard. Onboarding is described in three steps: connect a Google account and link the blog, tell the service who the business sells to so the AI can pick topics, then approve a plan and let the service handle the rest. The site promises content live in under ten minutes and articles that begin appearing on the blog with no further customer effort beyond approval. The single public plan, named Full Autopilot, includes fifteen human-reviewed articles per month, auto-publishing to the connected site, keyword research handled by the vendor, and one-click cancellation. Publishing integrations span WordPress, Wix, Shopify, Squarespace, Webflow, and Framer, which represent the main surface the customer touches.

On the question that gives this comparison its title, the public Cited.so product does not expose a prompt-level AI citation dashboard. There is no published mention-rate or citation-rate metric, no share-of-voice score, no per-engine breakdown separating ChatGPT from Perplexity, Gemini, or Claude, and no competitor benchmarking surface inside the product. Buyers who arrive searching for a Cited.so citation tracker are, in effect, asking whether the service shows the citation data behind its promises; on the evidence of the public site, it does not. Cited.so instead treats AI citation as a downstream consequence of publishing structured, AI-friendly content, and supports that framing with named customer testimonials reporting directional gains such as more customers, lower acquisition cost, and more organic leads. Those quotes are individual and self-reported; the site does not publish an aggregate figure, a controlled study, or third-party verification.

The fair reading is that Cited.so is a low-cost managed alternative to a content agency, optimized for owners who want the outcome and are comfortable treating the mechanism as a black box. Its limitations, judged only against what the public site documents, are the absence of exposed citation tracking, the single pricing tier with no seat or workspace structure, and quality controls described no more specifically than "human-reviewed."

What DeepSmith is, and what it is not

DeepSmith leads with a different promise: "One platform for AI search analytics and content production." The positioning is a self-serve platform that lets a team see where the brand shows up in AI search, find the gaps, and close them with on-brand content, all in one place. Onboarding runs from signup to a working workspace in minutes, with the brand brief, competitors, starter tracking prompts, and a first batch of ideas populated before payment. The distinction from Cited.so is structural: the customer operates DeepSmith, whereas a customer of Cited.so approves topics and receives finished articles.

The analytics side, the AEO module, is where the two products diverge most sharply. DeepSmith surfaces four headline metrics: mention rate, how often an engine names the brand; citation rate, how often an engine links to one of the brand's pages as a source; share of voice, visibility relative to a tracked competitor set; and visibility trend, movement over time. These are broken out across sub-views for tracked prompts, cited pages, and competitor citations, so a team can see per-prompt mention and citation rates, which of its own pages AI actually cites, and which competitor pages win the prompts it cares about. This is the definition of AI citation tracking software as the category has standardized it, and it is the layer Cited.so does not publicly expose.

The production side, Content Studio, is what makes DeepSmith more than a tracker. Ideas move from New Ideas to Planned to Produced, with a Writer in the middle that turns one planned idea into a finished, brand-grounded article: researched, internally and externally linked, with a cover image and publish-ready metadata. Autowrite extends this to hands-off operation, writing a scheduled article on its date and landing it in Produced Content with no one in the app. Publishing runs to WordPress, Strapi, Webflow, or a custom webhook, with Markdown and HTML export as fallbacks. Distribution is built into the article rather than bolted on: every finished piece ships with social posts drafted, and the Apps Library adapts one article into platform-native versions for LinkedIn, X, Medium, Substack, newsletter and email, and more.

DeepSmith's claim boundaries are worth stating directly, because they mark the honest limit of the comparison. The platform tracks mention and citation across the covered engines; it does not promise rankings, traffic, or revenue, and it does not control the citations it measures. The named engines are ChatGPT, Gemini, Perplexity, Claude, and Google AI Mode, and no engine beyond those is claimed. Its own testimonials describe volume and quality gains rather than guaranteed outcomes: one customer reports moving from four articles a month to fifteen with the same two people, another that drafts arrive close to final because the system carries the context, a third that tracking prompts where the brand ranks in AI answers has generated meetings.

Engines tracked versus engines published to

The two products name AI engines for different reasons, which is easy to conflate. DeepSmith names engines because it tracks them: coverage scales from ChatGPT on the Pro tier, to ChatGPT plus Perplexity on Grow, to ChatGPT plus Perplexity plus Gemini on Scale, to all five, including Claude and Google AI Mode, on Enterprise. A buyer choosing a tier is choosing how many engines the analytics will monitor. Cited.so names ChatGPT and Google as the surfaces it aims to rank a business on, but naming a target is not the same as tracking coverage per engine. There is no public evidence that Cited.so measures per-engine performance or reports it back to the customer.

The distinction matters for anyone comparing multi-engine reach. A team that needs to know how it performs on Perplexity versus Gemini versus Claude, separately, is describing a tracking requirement that DeepSmith addresses at the Scale and Enterprise tiers and that Cited.so does not appear to serve at all. A local owner who only wants to be recommended when a prospect asks ChatGPT for a nearby provider may not need per-engine data, which is precisely the buyer Cited.so targets.

Tracking depth: what each product lets you see

The clearest single difference is visibility into the mechanism. DeepSmith is built so the customer can inspect the data: per-prompt mention and citation rates, page-level citation attribution showing which pages earn the brand's citations, a competitor leaderboard, and the sources AI cites most often. A marketing lead can open the platform and answer, with data, whether a specific prompt names the brand, links to it, or hands the citation to a competitor. Cited.so is built so the customer does not have to look: the value proposition is that the work happens and results follow, with outcomes reported through testimonials rather than a live dashboard.

Neither approach is wrong in the abstract; they serve different buyers. But the difference is decisive for the reader who wants measurement. Understanding the gap between a brand being named and a brand being cited, and tracking each separately, is the foundation of a serious AEO program, and it is a capability DeepSmith exposes and Cited.so, on its public product, does not. A reader evaluating DeepSmith as a Cited.so alternative is usually one who has decided the data itself is part of the deliverable, not an implementation detail to be trusted to a vendor.

The content production model

Both products end in published articles, but the model differs in who does the work and who holds the context. Cited.so produces fifteen articles per month through its own editorial pipeline, human-reviewed, and publishes them to the customer's site. The customer's role is to define the audience once and approve topics. This is efficient for an owner with no content team, and it removes the entire production burden, at the cost of direct control over voice, structure, and editorial angle beyond the initial brief.

DeepSmith keeps production in the customer's hands but removes the manual labor around it. The Writer grounds every article in stored brand context: company positioning, product details, persona, brand voice, and content-type templates, so output reads like the brand and describes its real products without re-briefing per article. Keyword coverage, heading structure, internal linking, and metadata are part of the writing pipeline rather than a post-draft review pass. For teams whose recurring pain is the last stretch of work that turns a draft into a publishable article, the difference is that this work is built into generation rather than owned by a person. The trade is that DeepSmith expects a team to run the system, whereas Cited.so runs it for them.

Distribution, repurposing, and the surrounding workflow

Distribution is where the platform model shows a breadth the service model does not attempt. For Cited.so, distribution is publishing to the connected blog or CMS; the deliverable is the article on the site. DeepSmith treats a published article as a source for many channel assets: social posts arrive already drafted with each piece, and the Apps Library converts one article into platform-native versions across LinkedIn, X, Medium, Substack, newsletter and nurture email, and other channels, each adapted to that channel's tone and length. For a marketing team where distribution is the step that habitually falls off, having it produced from the same finished article is a workflow difference, not merely a feature count.

This reflects the broader design gap. Cited.so consolidates the content function by removing it from the customer entirely. DeepSmith consolidates it by collapsing the tools a team would otherwise stitch together, tracking, ideation, production, linking, imagery, and repurposing, into one platform the team still operates.

Pricing, seats, and team structure

On headline price the entry points are identical, and the comparison is easy to misread. Cited.so is a single plan at $99 per month for fifteen articles, auto-published, with one-click cancellation. DeepSmith's Pro tier is also $99 per month, or $80 effective on annual billing, and includes twenty articles, fifty tracked prompts, five seats, and ChatGPT tracking. From there DeepSmith scales: Grow at $199 adds Perplexity and lifts limits, Scale at $399 adds Gemini, and Enterprise is custom with all five engines, dedicated onboarding, and an account manager. The two $99 offers are not equivalent, because the DeepSmith figure buys tracking plus production seats for a team, while the Cited.so figure buys a fixed managed output with no documented seat or workspace model.

For agencies and multi-brand teams the structural difference compounds. DeepSmith's multi-workspace model runs multiple brands or clients from one account, each isolated with its own context, content, and plan, billed independently. Cited.so publishes a single tier with no stated team, seat, or multi-client structure, consistent with a product aimed at a single local business rather than an operator managing several.

Onboarding, trial, and commitment

Both products aim for fast setup and low commitment, with different mechanics. Cited.so promises content live in under ten minutes after a three-step connect-target-launch flow, and one-click cancellation with no questions. It does not publicly state a free trial. DeepSmith offers a 7-day free trial framed as real data and real drafts before payment, populates a working workspace during onboarding, and states no long-term contracts or cancellation fees. The practical read is that a buyer can validate DeepSmith by generating actual tracking data and drafts inside the trial, while a Cited.so buyer commits to the first month to see the managed output, then cancels if it does not land.

DeepSmith or Cited.so: which should you choose

The honest recommendation follows the operating model, not a feature scoreboard. The deepsmith or cited.so choice comes down to whether a team wants to run AI search visibility itself or delegate it.

Cited.so is the stronger fit when the reader is a local business owner without a content team, is weighing $99 per month against a several-thousand-dollar agency retainer, measures success as ranking on Google and being recommended by ChatGPT, and is comfortable judging the work on outcomes rather than inspecting per-prompt data. For that buyer, a managed service that ships fifteen reviewed articles a month and publishes them is a reasonable, low-friction option.

DeepSmith is the stronger fit when the reader runs a content or marketing team, or an agency, that treats content as a growth channel and wants to see where the brand appears across AI engines per prompt, per page, and per competitor, then produce the content to close the gaps in the same workspace. It suits teams that need multi-engine coverage, want brand-grounded production with internal links, metadata, and imagery built in, and want distribution generated from every finished article. It also suits the team scaling output that wants the manual work around writing removed at the source rather than handed to an outside vendor. For a marketing lead specifically, the deciding factor is usually whether the citation data is part of the deliverable; if it is, DeepSmith is the platform built to expose it, and the natural Cited.so alternative for a team that wants measurement and production under one roof.

Teams that want to see the tracking and the drafts before committing can start with the DeepSmith free trial and generate real data on their own prompts.