Humanswith.ai vs Profound vs Otterly vs AthenaHQ (2026 comparison)

If you want your brand cited by ChatGPT, Perplexity, or Google AI Overviews in 2026, all four platforms below can show you where you stand. Profound, Otterly.ai, AthenaHQ, and Humanswith.ai measure where AI engines mention you, and where you are losing ground. The one question that separates them is simple. How much of the execution do you want to keep in-house, and how much do you want handed off? Your answer, plus your budget, points to one platform faster than any feature matrix.

Profound is a marketing platform built for the AI era, with the deepest measurement in this group. It tracks more than ten AI engines, draws on a proprietary set of 1.5 billion-plus real user prompts, and surfaces content recommendations through built-in agents, though self-serve access to those agents is capped. If accuracy is your priority and you are comfortable doing your own content and outreach, Profound sets the standard.

Otterly.ai calls itself a Content Intelligence Platform for AI Search, and it earns the label. It monitors six engines, produces GEO briefs your team can act on, and carries the lowest entry price of the four. It does not write or publish for you. That stays with your team. For clear, affordable visibility into your AI search presence without a managed service, Otterly is the cleanest starting point.

AthenaHQ runs under the tagline "Agents to Win on AI Search." It adds two things its peers do not bundle: revenue attribution tied to AI-driven traffic, and in-platform drafting across eight engines with no add-ons. The draft still needs your team to review and publish it. The attribution layer gives revenue-focused marketers a clearer line from AEO work to pipeline.

Humanswith.ai runs as a hybrid platform and agency. It measures across nine engines, then ships the content, schema markup, and outreach that earns citations, instead of handing that work back to your team. One operator covers what would otherwise take five or six marketing roles across strategy, writing, technical SEO, and distribution. Done-for-you tiers mean the audit and the published fixes can sit on the same invoice.

All four are measurement-first products. The real difference is how far each one travels from insight to shipped work before it hands the baton back, and whether your team has the people to carry it the rest of the way.

Four tools, one crowded category. Here is how they compare before the deeper sections pull each one apart.

All prices are as of 2026 and can change. Check each platform's pricing page before you commit.

Profound launched in August 2024 with a clear thesis. Before you can fix your AI visibility, you need to measure it more precisely than any tool was offering. CEO James Cadwallader and CTO Dylan Babbs built toward that gap, and the product shows it.^[1]

What Profound does better than anyone else

The measurement is genuinely strong. Profound tracks share of voice, sentiment, and competitor benchmarking across more than ten AI engines: ChatGPT, Perplexity, Gemini, Copilot, Claude, Google AI Overviews, and more, all in one dashboard. Breadth matters here. Visibility in ChatGPT does not predict visibility in Perplexity, because the engines surface different sources and weight authority differently.

Two capabilities stand out as proprietary:

• Prompt Volumes is a set of 1.5 billion-plus real user prompts. Instead of guessing which questions your category "probably" gets asked, Profound can show you which prompts actually drive AI traffic in your space. That changes how you prioritize content.
• Agent Analytics watches AI bot-crawlers at the server and CDN log level. You see which AI systems crawl your site, how often, and whether they find what you want them to find. Most rivals work at the query-and-response layer. Profound reaches down to the infrastructure.

Execution: real, but gated

Profound describes itself as a marketing platform for the AI era, spanning measurement, analytics, content generation, and automation. That is accurate. It does have content agents that can read existing pages and write new ones.

The caveat is the plan. On self-serve, the Starter tier includes zero article credits, and Growth includes three to six articles a month on a credit meter. Execution exists, but on lower tiers the focus is firmly on measurement and recommendations. Teams that need to publish at volume will want the Enterprise tier, or a separate content workflow alongside Profound's data.

Pricing (as of 2026)

One practical note. The public pricing page now routes straight to enterprise sales rather than a self-serve checkout. Treat the $99 and $399 figures as orientation points. What a contract costs today takes a conversation, and pricing has grown less transparent as the product moved upmarket.

Enterprise contracts include SOC 2 and HIPAA options, which matter for healthcare, fintech, and any regulated vertical where AEO is still young.

Who it suits best

Profound fits enterprises that need the deepest multi-engine measurement, want a real prompt set rather than inferred keyword proxies, and have technical teams that can act on bot-crawler data. Agent Analytics in particular is built for companies with engineers who can connect CDN logs and turn those signals into action.

The honest limitation

The Starter tier is single-engine and ships with no content credits, so a small team testing the water sees a narrow slice of what the product really does. Combined with the move away from transparent self-serve pricing, that makes Profound hard to evaluate without entering a sales process, which raises the barrier for teams that want to trial before they budget.

Otterly.ai does one job and does it well. It tells you exactly where your brand stands in AI search, updated daily, across the engines that matter. Launched in 2024 by OtterlyAI GmbH in Austria, it earned a Gartner Cool Vendor nod in 2025 and a 4.8/5 rating on G2, a fast rise that reflects real demand for straightforward AI-search tracking.^[2]

The platform calls itself a Content Intelligence Platform for AI Search, and that fits. It tracks brand mentions and citations across six engines: ChatGPT, Perplexity, Google AI Overviews, Google AI Mode, Gemini, and Copilot. Coverage spans 50-plus countries with daily refreshes, benchmarking against named rivals, and an AI Prompt Research layer that maps which queries your category owns. A Content Audit layer produces a GEO score and turns that score into content briefs: specific, actionable fixes.

That brief is where Otterly's direct involvement ends. It does not write the content, handle schema, or run any publishing workflow. The briefs land on your team's plate. For teams with writers and developers already in place, that split works fine. For teams trying to close the loop without adding headcount, it is the core constraint.

Pricing (as of 2026, subject to change)

Google AI Mode and Gemini tracking are paid add-ons on top of the base plans. Annual billing saves 15%, and a free trial is available. An API is open on higher tiers, which matters for agencies running many client dashboards.

The unlimited workspaces on Standard and Premium make Otterly a credible agency tool. One subscription can serve a whole client portfolio at a price an SEO retainer already supports. A solo brand team checking its AI-search presence for the first time will find the $29 Lite tier a genuine low-risk entry.

The honest limits sit in two places. First, the prompt-based pricing scales steeply: going from 15 to 100 prompts is a 6.5x jump. Brands tracking more than a handful of queries across markets will reach Standard or Premium quickly. Second, Otterly is still an early-stage product from a small Austrian startup. The feature set moves fast, and so does the risk that comes with betting on a young vendor. Teams that need execution next to measurement will look elsewhere. Teams that simply need clear, affordable, multi-engine data, and already have the people to act on it, will find Otterly hard to beat at this price.

AthenaHQ was built by ex-Google Search and DeepMind engineers and is backed by Y Combinator.^[3] Its tagline, "Agents to Win on AI Search," signals more than a pure analytics tool. The platform promises both insight and action, and it is the most action-leaning of the three competitors covered here.

What AthenaHQ measures

The core tracks visibility across eight engines: ChatGPT, Google AI Overviews, Perplexity, Claude, Gemini, Copilot, Meta AI, and Grok, with no per-engine add-on fees. That flat access matters at scale. Tools that charge per engine make multi-engine coverage expensive fast. Metrics include prompt analytics, source and response analytics, share of voice, and mention and citation rate.

Two features stand out. First, native revenue attribution through Shopify and GA4, which lets e-commerce teams connect AI visibility to real conversions rather than stopping at impressions. Second, ACE, the Athena Citation Engine, an ML model that predicts how likely a piece of content is to be cited by an AI engine before you publish it. For teams prioritizing where to invest, that signal is genuinely useful.

How execution actually works

AthenaHQ's Content Agents and Action Center can draft content inside the platform. That is meaningfully further along than a tool that only surfaces recommendations and leaves you a blank doc. The company calls it a "force multiplier, not a replacement for an editor," which is an honest read of the handoff. You review the draft, then publish to your CMS yourself. There is no outreach engine, so link-building and PR stay off-platform.

So the fair summary: AthenaHQ measures, predicts citation odds, and assists drafting. The finished content, schema, and outreach still land on your team.

Pricing (as of 2026, subject to change)

There is no free trial. The credit model charges one credit per AI response, so one prompt across four models costs four credits. At 3,500 credits on Self-Serve, a team doing regular multi-engine testing hits limits quickly and feels the pull toward Growth or Enterprise.

Who it suits best

AthenaHQ is a strong fit for GEO-serious mid-market and e-commerce teams, especially Shopify merchants, that want measurement, guided drafting, and revenue attribution in one place. The native Shopify and GA4 connectors remove a layer of manual stitching other tools leave to you.

The honest limitation

Entry cost is the friction point. At $295 a month with no trial, smaller teams commit real budget before they see whether ACE predictions or Content Agent output match their workflow. And the Self-Serve credit ceiling means any team doing thorough multi-engine monitoring will likely need Growth at $545 a month to work comfortably. Teams with tighter budgets or simpler needs may find the value case harder to close.

Humanswith.ai is a hybrid platform and agency. It tracks where AI systems mention your brand across nine engines, then ships the content, schema markup, and outreach that moves those numbers. The difference from pure monitoring tools is operational. The work gets done, not just diagnosed.

The model replaces five of six marketing roles, analyst, copywriter, content manager, SEO, and designer, under a single operator. That operator does not hand you a brief or a draft. They deliver finished assets. For teams that tried a monitoring tool and stalled at the "now what?" stage, that is a real structural difference.

What the case studies show

The published cases at humanswith.ai/cases^[4] are specific enough to judge:

• A dogfooded campaign reached 1,000+ AI mentions in 12 weeks
• Birdview PSA hit a 21.5% ChatGPT share of voice in 8 weeks
• GAC went from 1 to 9,042 mentions in 6 weeks
• Whitewill went from 0 to cited within 12 weeks
• Gorbilet reached 94.6% branded share of voice in 10 weeks
• LS ELECTRIC grew from 66 to 170 mentions across a 12-week engagement

The pattern is consistent. A defined baseline, a defined endpoint, a defined timeframe. That is a higher bar than "clients saw improved visibility," which is common in this category.

Tiers versus a typical SMB stack

The site benchmarks a typical SMB SEO stack at $2,000–$5,000 a month, covering separate tools for monitoring, content, SEO, and design plus freelance or agency time.^[5] The mid tiers sit below or at that range. The enterprise tier goes above it in exchange for fully managed work.

Where it sits in the 2026 landscape

Closing the loop, measure, ship content, run outreach, prove lift, is the contested frontier right now. Several rivals are adding execution, so the honest differentiator is not "the platform that does this." It is the case record: documented share-of-voice numbers across named clients, with timelines attached.

The nine-engine scope, against the four or five engines most tools prioritize, matters most for brands that need to show up across ChatGPT, Perplexity, Google AI Overviews, and newer engines at once. For teams focused on one or two engines, that breadth may be more than they need.

Honest limitation

A done-for-you engagement is a real commitment, with higher cost and more coordination than a self-serve dashboard. If your team only needs a monitoring feed and produces content in-house, the Starter tier or a lighter tool is the more proportionate choice. The full-service model is built for organizations that want the output, not just the data.

All pricing as of 2026 and subject to change.

The execution row is where the four diverge most. Otterly.ai stops at the recommendation layer. You get prompt tracking and structured briefs, then your writers take over. That suits teams with editorial capacity and a need for affordable monitoring across six engines. AthenaHQ goes one rung further, with drafting inside the platform, but publishing, schema, and distribution stay your team's job. The workload drop is real. The last mile is still yours.

Profound sits in a similar place on self-serve, where drafting is available but volume-capped. Its real edge is upstream, in the data. A set of 1.5 billion real user prompts grounds Profound's figures in actual search behavior that sampled prompt sets cannot match at the same scale. For teams where measurement accuracy is the main purchase criterion, large enterprises and regulated industries, that data alone can justify the cost, especially next to SOC 2 and HIPAA options the other three do not market.

Humanswith.ai occupies the far end of the row. Measurement across nine engines feeds content production, technical work like schema and structured data, outreach, and a reported-lift close. The platform handles what the others leave on your plate. The trade-off is the pricing shape. A flat retainer, not a self-serve credit model, fits a different budget conversation, closer to an agency engagement than a SaaS subscription.

Attribution sets AthenaHQ apart for e-commerce. Native Shopify and GA4 connections tie AI-referred sessions directly to revenue, a link the others approach differently. Profound surfaces bot-log data through Agent Analytics, Otterly exposes an API at higher tiers, and Humanswith.ai wires attribution as part of the engagement. If your main question is "which AI engine sends buyers, and what do they spend," AthenaHQ answers it without custom plumbing.

The honest read: no platform here is measurement-only, and none fully replaces the others in every context. The decision hinges on where your team's capacity runs out, at the brief stage, the draft stage, the publish stage, or the prove-lift stage.

Most bad fits trace back to a handful of mistakes. They are easy to avoid once you name them.

The first is buying for engine count alone. Ten engines beat six only if the extra four are engines your buyers actually use. A clothing brand whose customers live in ChatGPT and Google AI Overviews gains little from Grok or Meta AI coverage.

The second is confusing measurement with execution. A dashboard tells you that you are missing from an answer. It does not write the page that fixes it. Teams that buy a monitor and assume the content "will get done" often find the gap list sitting untouched a quarter later.

The third is underestimating the last mile. AthenaHQ and Profound both draft, but a draft is not a published, schema-marked, internally-linked page. Someone still has to own the final step. When no one does, drafts stall in review.

The fourth is ignoring the baseline. If you change your tracked prompts after you start shipping, you cannot tell whether your work moved the numbers or the prompt set drifted. Lock the baseline first.

The fifth is over-buying. A $295-a-month attribution suite is the wrong tool for a team that only wants to know whether it shows up in ChatGPT. Match the tier to the job.

The right answer depends on where your team's capacity ends and where you need a tool, or a service, to take over.

You want the deepest measurement and enterprise-grade security

Choose Profound. Its real-prompt data, bot-level crawler analytics, and multi-engine tracking make it the most thorough analytics option for AEO and GEO. If you are in a regulated industry and need SOC 2 or HIPAA, Profound is the practical pick. Pricing starts around $99/mo (as of 2026, subject to change).

You are a small team or agency that will execute the recommendations yourself

Choose Otterly.ai. At around $29/mo (as of 2026), it delivers daily monitoring across engines with unlimited workspaces, a strong value for agencies managing many clients or lean in-house teams that want visibility without a large commitment. Otterly gives you the signal. Your team acts on it.

You are in e-commerce or mid-market and want measurement tied to revenue

Choose AthenaHQ. It pairs measurement with in-app drafting and native revenue attribution, so you can connect AEO work to pipeline, not just rankings. It is built with Shopify and mid-market workflows in mind. You will need an editor to publish the output, but the drafting happens in-platform. Pricing starts around $295/mo (as of 2026).

You want measurement, content, schema, and outreach handled for you

Choose Humanswith.ai. It covers monitoring across nine engines, then ships the finished content, schema markup, and outreach, so you are not coordinating a writer, an SEO, a schema specialist, and an outreach manager separately. The lift is measured against a baseline, so you can see what moved. Pricing starts around $497/mo (as of 2026). That is a higher number than the others, but it replaces several roles rather than adding a dashboard.

These categories are not always clean. A mid-market team with a strong content operation might choose Profound for measurement and execute in-house. An enterprise team with its own writers might find AthenaHQ's attribution worth the trade-off. The table shows the most common fit, not the only one.

A quick pre-purchase checklist

Run through these before you commit to any platform:

• List the AI engines you actually need to appear in, not all ten
• Decide who executes the work: your team, or the vendor
• Confirm whether the tool publishes, drafts, or only recommends
• Check the real entry price (Profound's now routes to sales)
• Verify revenue attribution if you sell online (AthenaHQ leads here)
• Lock a baseline prompt set before you start
• Name one person who owns "approved to published"
• Plan to re-measure on the same prompts after 8 to 12 weeks

The transition starts with what you already have. Your monitoring baseline, the tracked prompt set, the competitor citation map, and the gap list the tool surfaced, is your execution work list. Do not rebuild it. Port it.

What to carry over

That last row matters more than it sounds. If you measure on different prompts after publishing, you cannot tell whether the numbers moved because of your work or because the prompt set drifted.

Build or buy the execution layer

The honest question is whether your team has the writers, technical SEO, and schema skills to turn a gap list into shipped work. If yes, treat the monitoring tool as a pure signal layer and build execution in-house. If not, the faster path is an operator or agency that already works inside your tool's export format, or a platform that handles both sides so the gap list feeds a draft queue without a manual handoff. Neither is automatically right. In-house keeps the knowledge on the content. A bought layer moves faster but adds a coordination dependency.

Three pitfalls that stall teams

1. Double monitoring. If you add an execution platform that also monitors, audit the overlap before you renew the original tool. Two subscriptions measuring the same engines is budget waste with no extra signal.
2. Unclear publish ownership. Drafted content that no one is responsible for publishing sits in review forever. Before the first brief goes out, name one person who owns the approved-to-live step. One person, not a committee.
3. A shifting baseline. Run your before-and-after on the exact prompts and engines you tracked at the start. Swapping in new prompts mid-cycle, even better ones, makes the lift invisible. Lock the baseline for at least one full cycle, then expand.

The migration is low-drama once those three are handled. The monitoring work was not wasted. It is the foundation the execution layer is built on.

• [1] Profound — product and pricing: https://www.tryprofound.com
• [2] Otterly.ai — product and pricing: https://otterly.ai
• [3] AthenaHQ — product and pricing: https://athenahq.ai
• [4] Humanswith.ai — case studies: https://humanswith.ai/cases
• [5] Humanswith.ai — pricing: https://humanswith.ai/pricing