DeepSmith vs Searchify: AI Engine Visibility vs Visibility Plus Editorial Output

The DeepSmith vs Searchify decision turns on a single question that feature lists tend to obscure: whether a platform stops at reporting where a brand is invisible in AI answers, or continues into producing the content that changes the picture. Both products sit inside the same category of AI engine visibility tools, the software that measures how often ChatGPT, Perplexity, Gemini, Claude, and Google's AI surfaces name and cite a brand. They separate on what happens next. Searchify converts the measurement into a prioritized recommendation queue, with an optional human-delivered service that executes it. DeepSmith converts it into a production pipeline that writes the articles in the same workspace.

For a marketing lead running an evaluation, the useful framing is not which dashboard is denser but whether the binding constraint is diagnosis or output.

DeepSmith vs Searchify at a glance

The two products overlap on measurement and diverge on how engine access is priced and on whether the workflow ends at a recommendation.

What Searchify is

Searchify is an AEO measurement platform positioned around a specific buyer. Its site copy describes it as the first and only platform built for small and medium-sized businesses in AI search, and its messaging centers on actionable steps to get a brand recommended by AI. The San Francisco company, led by founder and chief executive Noah Moscovici, cites an eight-month study of SMB AI visibility published on its blog in January 2026 as the research behind that positioning.

The measurement surface is broad. An AI Search Score reports share of voice against named competitors, Visibility by Channel breaks mentions down per engine, and a Competitor View handles benchmarking against named rivals. A Citations Analysis names the third-party domains AI engines lean on when answering questions in the category, useful signal for a team deciding where to seek coverage. Two modules extend past presence into how a brand is described and what happens after the answer: a Sentiment Report classifies brand framing as positive, neutral, or negative, and Funnel Analytics reports per-engine visit and conversion telemetry. Realistic User Question Simulation runs conversations shaped to an ideal-customer profile, showing what an engine would tell a buyer who matches it, and both tracking and simulation operate across more than 30 languages.

The Action Center is where Searchify AI visibility data becomes a work queue. It surfaces prioritized recommendations across technical fixes, listing and coverage gaps, content-gap opportunities, and trending topics. Site copy frames the next step two ways: act on the recommendations directly, or let Searchify act instead. That second path is the Fully Managed Service, a separately priced human-delivered add-on rather than a software feature, and it is the mechanism by which recommendations become published work. Automated reporting runs on a daily, weekly, or monthly cadence, and every paid plan carries unlimited seats.

What Searchify does not do is produce content inside the product. There is no article generation, no brief generation, and no drafting workspace, and no CMS publish integrations or webhook-based content delivery appear on the plan pages. Its case-study tiles are labeled as coming in 2026, so no customer outcomes or named quotes are available to evaluate yet.

What DeepSmith is

DeepSmith is one platform for AI search analytics and content production. It measures how AI engines answer the questions that matter in a category, identifies where a brand is absent or losing, and produces on-brand articles to close those gaps, all from a single stored context. The defining design choice is that production is not a separate purchase bolted onto a tracker but the second half of the same workflow.

The measurement half reports mention rate, citation rate, share of voice, sentiment, and visibility trend, with a per-platform breakdown, a competitor leaderboard, and the sources engines cite most often. The Prompts view holds every tracked question with per-prompt mention and citation rates plus full answer history, and Discover Prompts generates a starter set from stored product, persona, and buyer-stage context. A Pages view reports which specific pages AI cites, each page's share of total citations, and the prompts driving them, which pins visibility data to individual assets rather than the brand as a whole. Competitor Citations extends that outward: who wins citations for the tracked prompts, on which pages, and by platform.

The production half runs through Content Studio, and what feeds it is the part a tracker cannot match. Opportunity Agents read a brand's own AI-visibility data and its Content Map and return content ideas with the evidence attached, each carrying the specific data point that justifies it. Those ideas land in New Ideas, the single backlog of everything from agent runs, manual entry, or import. Planned Content is the calendar, and the Writer turns one planned idea into a finished, brand-grounded article with internal and external links, a cover image, and publish-ready metadata. Autowrite removes the last manual step: an article configured at planning time writes itself on its scheduled date and lands in Produced Content with nobody in the app. Produced Content is where a team previews, edits body and metadata, regenerates the cover, and publishes to WordPress, Webflow, Strapi, Sanity, or Contentful, or to custom webhooks, with Markdown and HTML export as a fallback. Repurpose attaches social posts to every finished article, and the Apps Library converts one article into platform-native versions for LinkedIn, X, Medium, Substack, email, Reddit, and other channels.

Three layers hold the system together. Content Map maps a brand's own site plus unlimited competitor sites onto one topic taxonomy, refreshed every 24 hours, so coverage gaps and untapped topics are measured rather than guessed. Deep IQ stores About Company positioning, per-product profiles, buyer personas, brand voice, visual guidelines, and reusable content-type templates, and every module reads from it, which keeps voice and product accuracy stable as volume rises. Multi-Workspace runs multiple brands or clients from one account, each isolated with its own context, content, and plan.

DeepSmith produces publish-ready articles rather than first drafts to rescue, which is the difference between adding production capacity and adding an editing queue.

Engine coverage compared

The two platforms separate on breadth and on how that breadth is priced, and they lead on different halves of it. Searchify tracks six engines, including Microsoft Copilot and Google AI Overview, on every paid plan, with no upcharge to unlock Claude or Gemini and no tier at which the list shrinks, so a team on the $149 Starter plan sees every surface the product measures. The bound on that is what the entry plan carries alongside it: 30 tracked questions and bi-weekly recommendation refreshes, so all six engines are read through a narrow question set on a slow cadence.

DeepSmith tracks ten: ChatGPT, Gemini, Perplexity, Claude, Google AI Overviews, Google AI Mode, Grok, Meta AI, Microsoft Copilot, and DeepSeek. That is the wider list, covering both engines Searchify leads with, Copilot and AI Overviews, plus Grok, Meta AI, and DeepSeek. Access is tiered rather than flat: Pro tracks ChatGPT, Grow adds Perplexity, Scale adds Gemini, and Enterprise and Custom cover all ten. Pro tracking ChatGPT only is the real constraint at the entry price, and ChatGPT is where most buyer research starts, so the entry tier is narrow rather than blind.

The sharper question is what those engines feed. Searchify's coverage produces a recommendation queue, not execution capacity, and the queue still has to be worked by a team or by the paid managed service. DeepSmith's coverage feeds a pipeline that writes against the gaps it finds. Buyers whose audience concentrates on ChatGPT, Perplexity, and Gemini reach full coverage of their actual surfaces on DeepSmith's Scale tier at $399 per month, the same price as Searchify's mid tier, with 90 articles included.

Measurement depth compared

Prompt capacity, analytical layers, and how the data attaches to assets are the other dimensions, and the two platforms lead on different ones. Searchify AI visibility plans scale tracked questions from 30 on Starter to 100 on Basic to 1,000 on Pro. That top figure is the largest published prompt library in this comparison by a wide margin, and for a brand with many products, regions, or buyer segments, prompt capacity binds first. One analytical layer is genuinely exclusive to Searchify: Funnel Analytics, which reports per-engine visit and conversion telemetry, a post-click readout DeepSmith does not offer. Both platforms report sentiment: Searchify as a Sentiment Report that classifies how engines frame a brand, DeepSmith as a standing metric alongside mention rate, citation rate, and share of voice. Multilingual scope is the other Searchify column: more than 30 languages for tracking and ICP question simulation, against DeepSmith's reliance on engine-native languages.

The counterweights are the price attached to that prompt ceiling and what happens to the findings. Searchify's 1,000-question tier costs $999 per month, roughly two and a half times DeepSmith's top published plan, and recommendation cadence is plan-tied as well: Starter refreshes bi-weekly, Basic weekly, and only Pro runs daily, so a team buying at the entry price works from a slower signal than the headline suggests. DeepSmith's prompt caps of 50, 100, and 200 are lower in absolute terms, but each tracked prompt resolves to per-prompt mention and citation rates, full answer history, and page-level attribution of which asset earned the citation. Funnel telemetry answers what the traffic did after the answer. Page-level attribution answers which asset to fix or replace, the input a production step consumes.

Production and distribution compared

This is the widest operational gap between the two products, and for a team running an ongoing content program it is likely the deciding one. Searchify produces no articles, briefs, or drafts inside the product. The Action Center identifies content-gap opportunities and trending topics, and execution happens elsewhere: in-house, through an agency, or through the Fully Managed Service. That add-on is a legitimate answer for teams without writers, priced at $200 per month on top of Starter, $400 on top of Basic, and $800 on top of Pro. It is a human service line rather than software capacity, so throughput is negotiated rather than published, and Starter plus the add-on reaches $349 per month before any article count is set.

DeepSmith publishes flat article ceilings by tier: 20 per month on Pro, 40 on Grow, and 90 on Scale, with custom limits at Enterprise. What each tier buys is legible before purchase, and the output is finished rather than advisory: an article with links, a cover image, and metadata, produced against stored brand context and pushed straight to a CMS. Distribution sits in the same workspace, where the Apps Library converts one article into channel-native versions across more than ten channels, so the step that most often falls off a content calendar becomes part of the article.

A team whose constraint is knowing what to write will not feel the absence of in-product production, because its writers are already the answer. A team that has identified more gaps than it can staff writers to fill feels it immediately.

What each price buys

Searchify's three published plans buy measurement breadth, seat count, and refresh frequency: $149 Starter with 30 tracked questions and bi-weekly recommendations, $399 Basic with 100 questions and weekly recommendations, and $999 Pro with 1,000 questions and daily recommendations, each carrying all six engines and unlimited seats. Unlimited seats is a real advantage for an organization that wants wide read access to visibility reporting without a per-user bill, against DeepSmith's caps of 5, 7, and 10. The counterweight is that the group operating a production pipeline is usually smaller than the group reading a dashboard.

DeepSmith's plans buy production volume alongside measurement at a lower price at every published tier: $99 Pro with 20 articles and 50 prompts, $199 Grow with 40 articles and 100 prompts, and $399 Scale with 90 articles and 200 prompts, with custom limits and a dedicated account manager at Enterprise. Both vendors discount annual billing, Searchify advertising up to roughly 20 percent and DeepSmith listing $80, $160, and $299 per month. DeepSmith states no long-term contracts and no cancellation fees on its pricing page, while Searchify's plan pages do not surface cancellation terms, which is worth resolving before committing. Neither publishes SLAs or data-retention terms, so procurement should request those directly.

The free entry points differ in the same way the products do. Searchify offers a free AI Visibility One-Pager with no credit card, a generated report rather than product access, so it does not exercise the Action Center or the reporting cadence. DeepSmith offers a 7-day trial that runs on real data and produces real drafts in a workspace populated during onboarding, so what gets tested is the product itself against a brand's own gaps. Absent contracts and cancellation fees extend the evaluation in practice, since a first paid month carries no exit penalty.

Strengths and limitations

Searchify's strengths concentrate in flat access and service: six engines on every tier with no gating, sentiment and funnel analytics on all plans, 30-plus languages, unlimited seats, a free one-pager, and a managed-execution option. Its limitations are the absence of in-product production, caps of 30 and 100 tracked questions on the two lower tiers, bi-weekly recommendation cadence at entry, competitor slots capped at four on Starter and ten on Basic, no publicly surfaced CMS or webhook publishing, and no published case studies, since its case-study tiles are still marked as coming in 2026.

DeepSmith's strengths concentrate in closing the loop: ten tracked engines, measurement and production in one workspace, Opportunity Agents that turn visibility and Content Map data into ideas with the evidence attached, publish-ready rather than advisory output, scheduled generation through Autowrite, publishing to WordPress, Webflow, Strapi, Sanity, Contentful, and webhooks, distribution across ten-plus channels built into each article, Deep IQ grounding every draft in stored positioning and voice, and Multi-Workspace isolation for agencies. The constraints that bear on this choice: engine access is tiered, so the full ten arrive at Enterprise rather than at the entry price; article output is capped at 20, 40, and 90 per month; seats at 5, 7, and 10; and there is no post-click funnel telemetry.

Which should you choose

The decision resolves by situation rather than by an overall winner. Searchify is the stronger fit for a small or mid-sized business without an in-house content team, where the realistic path is a prioritized recommendation list plus outsourced execution through the managed add-on. It also fits a brand that wants every engine it measures unlocked at a mid-tier price rather than at Enterprise, that operates in more than a handful of languages, that requires per-engine conversion telemetry, that needs daily recommendation refreshes, or that wants a very large prompt library on one plan and can absorb the $999 tier. Teams weighing a Searchify alternative purely because the entry price is $149 should note that the trade at that tier is flat engine access for production capacity.

DeepSmith is the stronger fit when output is the binding constraint. A mid-market content team that wants to ship 20 to 90 articles per month and track AI visibility in the same tool, an agency running multiple client brands from isolated workspaces, or a team that wants brand-grounded articles rather than generic drafts will get more from a platform that treats measurement as an input to writing. For a marketing lead considering a Searchify alternative specifically because the recommendation queue grows faster than the team can work it, in-product production answers that gap directly.

The deepsmith or searchify question therefore reduces to where the program stalls, and among AI engine visibility tools that is the question that separates the field. If nobody knows which surfaces are losing, Searchify's flat engine access, funnel telemetry, and prompt ceiling are attractive, and the managed service is a real path to execution for teams without writers. If the gaps are already known and the queue is not moving, a platform that measures and writes closes the distance without adding headcount.

Teams whose constraint is production can test that on live data. A DeepSmith free trial surfaces real visibility data and real drafts within seven days, putting the production claim against a brand's own gaps rather than a demo.