Profound GEO: Pricing, Coverage, and Maintouch (September 2026)

Profound just crossed a billion-dollar valuation on a single bet: that AI-generated answers are becoming the primary discovery surface for buying decisions. It's a credible bet, and the product behind it is worth understanding on its own terms. Whether it fits your situation comes down to a few structural questions the marketing copy doesn't answer. My goal: you walk away knowing exactly what Profound does, what it costs at each tier, and whether it's the right tool for where you are, or whether you need something that closes the loop between insight and shipped work.

TLDR:

• Profound is a GEO monitoring tool: it tracks AI citations across engines but stops short of executing the work itself
• Pricing is gated by engine coverage, with Claude, Gemini, and Copilot all sitting behind custom Enterprise pricing
• Citation drift runs 40-60% monthly across major AI engines, so the gap between insight and action is a real cost
• Profound fits enterprise teams with 500+ employees and a dedicated analyst; it breaks down for smaller teams without one
• Every Maintouch self-serve tier starts with a 5-day free trial, with execution built into the same system

What Is Profound GEO

Profound is a GEO tool built to track and improve how brands show up inside AI-generated answers. GEO, or Generative Engine Optimization, is the category focused on what ChatGPT, Perplexity, Gemini, and similar engines produce, instead of traditional Google rankings.

The problem is straightforward. When someone asks an AI chatbot a buying question, the engine assembles an answer from a handful of sources and cites them inline. If your brand isn't one of those cited sources, you don't exist in that interaction. 59.7% of Google searches already end without a click. AI answers accelerate that trend; users get what they need without ever landing on your site.

The industry hasn't agreed on a single name for this yet. You'll see answer engine optimization (AEO) and LLMO used interchangeably. Profound uses "GEO" as its label. The mechanics are identical regardless, and the product is designed to help marketing teams understand where they're being cited, where competitors are showing up, and what content changes could shift those outcomes.

The Founders: James Cadwallader and Dylan Babbs

Profound was co-founded by James Cadwallader and Dylan Babbs. They met at South Park Commons, a startup incubator in San Francisco, and launched the company in 2024.

Cadwallader is CEO. Before Profound, he co-founded Kyra, a data-driven influencer marketing agency that worked with Fortune 500 brands. Babbs is CTO and came from Uber, where he worked as a design engineer on maps and location services. One founder with a marketing background, one with serious engineering depth in data-heavy products: it's a sensible pairing for a company trying to turn messy AI citation data into something actionable.

Profound's Funding and Valuation

Profound raised a $180M Series D in September 2026 at a $1.8B valuation, co-led by Sequoia Capital and Kleiner Perkins. Total funding now sits at above $335M.

A billion-dollar valuation for a GEO-specific company is a meaningful signal. Lightspeed, Sequoia, and Kleiner Perkins don't bet that size on categories they think are marginal. The thesis is that AI-generated answers become a primary buying discovery surface and that brands pay real money to show up inside them. Whether Profound can convert that capital into durable product advantage is a separate question, but the money confirms GEO is a real category, not a trend that's getting funded on hype alone.

How Profound Works: The Read/Write Model

Profound frames its product around a "read/write" model. It's the clearest way to understand what the tool actually does day to day.

The read side is monitoring. Profound runs prompts across AI engines and records whether your brand gets cited, how it's positioned relative to competitors, and what sentiment the AI attaches to mentions. You're watching, in near real time, how chatbots talk about you when someone asks a relevant buying question.

The write side is where Profound tries to turn those observations into action. Their Agents layer generates content recommendations, surfaces GEO best practices to act on, and flags gaps where competitors are getting cited and you aren't.

In practice, the read side is where Profound is strongest. The write side delivers recommendations, but execution still happens somewhere else, in separate tools, by someone on your team. That distinction matters more than it might sound, and I'll come back to it.

Core Features Explained

Once you understand the read/write frame, the individual modules make more sense. Profound's product breaks into seven of them, each handling a different slice of the GEO workflow.

• Answer Engine Insights: citation tracking and share-of-voice measurement across AI engines. You see how often your brand gets mentioned relative to competitors in AI-generated responses, broken down by prompt category.
• Prompt Volumes: panel-based data showing what users are actually asking AI chatbots. This gives you demand signal for AI queries the way keyword volume tools do for Google searches.
• Conversation Explorer: access to anonymized real user conversations behind those volume numbers. You can read actual back-and-forth exchanges to understand context and follow-up patterns.
• Agent Analytics: tracks AI crawler behavior using server logs and CDN connections. You can see when bots like GPTBot or PerplexityBot hit your pages, how deep they crawl, and what they're pulling.
• Profound Agents: drag-and-drop workflow automation for content and PR tasks. Think Zapier-style builder where you chain together steps like "find citation gaps, draft a brief, send to writer." The output is a set of instructions, not finished work pushed to your CMS.
• Profound Aim: launched July 2, 2026, this is an always-on background agent layer that converts monitoring signals into ranked marketing projects. It watches your citation data and surfaces recommended actions ranked by estimated impact.
• Profound Index: competitive citation benchmarking across your category. You can compare your citation share against named competitors over time to spot who's gaining or losing ground.

How AI Visibility Scores Are Calculated

GEO visibility scores look simple on the surface. The mechanics underneath are worth understanding before you trust them.

The process starts with prompts. A GEO tool runs queries relevant to your category across AI engines at scale. Each prompt fires against ChatGPT, Gemini, Perplexity, and others, and the system records whether your brand gets cited in the response. Run this across hundreds of prompts and you get a raw citation count: out of 500 prompts, your brand appeared 73 times.

Raw counts alone are misleading. A citation on a prompt nobody asks is worth less than one on a high-volume buying question. Most scoring systems apply a weighting layer, multiplying citation frequency by estimated prompt volume or strategic importance, and the result is a weighted visibility score that reflects both how often you're cited and where those citations land relative to actual demand.

Share of voice adds the competitive layer. If you're cited in 15% of responses and your top competitor hits 40%, that gap is the signal worth acting on, not your absolute number. Understanding which AI visibility metrics and KPIs to track helps you act on those gaps efficiently.

One frank caveat: these scores show where you're winning and where you're losing, but they can't tell you why the AI chose one source over another in any single response, or whether a citation drove a buying decision. The inputs are real, the math is sound. Treat the output as directional intelligence for prioritization, not a precise conversion metric.

AI Engine Coverage and What Each Tier Unlocks

Profound's pricing tiers are gated by AI engine coverage. The plan you need depends less on feature access and more on which engines your buyers actually use.

• Starter covers ChatGPT only.
• Growth adds Perplexity and Google AI Overviews.
• Enterprise unlocks the full set of 10 engines, including Claude, Gemini, Microsoft Copilot, Meta AI, Grok, DeepSeek, and Google AI Mode.

That structure has a practical consequence. If your buyers use Perplexity and ChatGPT but you also care about Claude citations, and a lot of B2B buyers are on Claude, you're looking at Enterprise pricing before you've reviewed anything else. Claude sitting behind a custom-priced tier is a real gate for teams that want full visibility without a sales conversation. That's when teams start looking at Profound alternatives.

The engine you need picks your tier for you.

Profound Pricing: Trial and Enterprise

Profound offers two tiers: a free Trial and a custom Enterprise plan. There are no published self-serve monthly prices.

Profound publishes no self-serve monthly pricing. The free Trial covers three engines for seven days, and after that the only path forward is a custom Enterprise conversation.

Claude, Microsoft Copilot, DeepSeek, and every other engine beyond that set sit behind Enterprise: custom pricing, no published rate, and a required sales process. If any of those engines matter to your buyers, the advertised tiers will not get you there. For context, Profound has charged 10-person companies more than $50,000 per year at the Enterprise tier, with no dedicated human support included in that price. Teams should factor that ceiling into evaluation before starting a trial.

There's also a cost that doesn't show up on the pricing page. Profound is a monitoring product. Someone on your team still needs to interpret the dashboards, rank the gaps by importance, and coordinate execution in separate tools. That layer, whether it's a contractor at $2,000/month or a slice of a full-time hire, is part of the real spend on top of Enterprise pricing.

Where Profound Leads

Profound's strongest card is its demand data. The Prompt Volumes module draws from a double opt-in consumer panel contributing hundreds of millions of prompts per month, actual query behavior, not modeled estimates. Conversation Explorer goes further: you can read anonymized real user conversations with AI chatbots, including follow-up questions and context changes a simple volume number would miss entirely.

Agent Analytics is genuinely useful for technical teams. It pulls server-log and CDN data to show which AI crawlers hit which URLs, how deep they crawl, and how often they return. Most competitors don't offer that granularity, and the best AEO tools review covers how the field stacks up by comparison.

On the enterprise side, Profound checks the standard procurement boxes: SOC 2 compliance, SSO/SAML, Tableau and Power BI connectors. The company reports 700+ enterprise customers, including roughly 10% of the Fortune 500.

Competitive benchmarking through Profound Index rounds out the picture. Citation share tracked against named competitors over time, across multiple engines: it's a scoreboard you can actually put in front of a VP of Marketing with real trend lines behind it.

Known Limitations and Trade-offs

That's where Profound earns its reputation. Here's where the friction shows up.

• One workspace per account on self-serve plans. Agencies managing multiple clients can't run them under a single subscription, making Profound awkward for multi-client operations without jumping to Enterprise. The best AI visibility trackers review covers which tools handle multi-client setups more cleanly.
• The dashboard is data-heavy and not intuitive out of the box. Teams without a dedicated analyst often struggle to extract actionable takeaways from the volume of metrics.
• Prompt volume numbers come from a modeled consumer panel, not exact query counts. Practitioners have questioned the methodology, and the figures should be treated as directional estimates.
• Dashboard performance has been flagged as slow during peak usage, with load times that interrupt workflow for teams running frequent checks.

Two more things worth flagging: agencies routinely pair Profound with SEMrush to cover AEO reporting gaps, which tells you that even power users don't treat Profound as sufficient on its own. And Profound runs on third-party data providers shared with other competitors in the space, so the data isn't proprietary. Maintouch replaces that multi-tool stack inside one system.

The deeper structural issue: Profound's tiers tell you what's happening. They don't do the work. Acting on citation gaps still requires content teams or contractors in separate tools. And Profound's own research puts citation drift at 40-60% monthly across major AI engines, meaning the data changes before most teams have time to respond. Closing that response gap is the whole problem.

Who Profound Is Best For

Profound works best for enterprise marketing teams at 500+ person companies where SOC 2, SSO/SAML, and role-based access are procurement prerequisites, not nice-to-haves. If you have a dedicated analyst who can live inside the dashboards, pull citation trends, and translate them into briefs for content teams working in other tools, the data depth is a real asset.

Agencies running multi-client enterprise accounts are the other natural fit. The reporting infrastructure, competitive benchmarking, and BI connectors produce output you can put in front of a VP of Marketing at a Fortune 500 account and have it land.

It breaks down on the startup and growth-stage side. If you're a 15-person B2B company without a dedicated SEO analyst, you'll spend more time figuring out what the dashboard is telling you than acting on it. And when you do figure it out, execution still happens elsewhere. For teams that need the work done, with the signal surfaced and then handled, Profound's self-serve tiers create a gap smaller teams typically can't staff around.

How Maintouch Approaches the Same Problem

I built Maintouch to close the gap between "here's what's happening" and "here's the work, shipped." Profound gives you the read. Maintouch does the read and the write, inside one system, with no handoff to a contractor or a content team working in separate tools.

Every self-serve paid tier also starts with a 5-day free trial. Starter covers ChatGPT, Google AI Overviews, and Perplexity. Scale adds Gemini. Hypergrowth adds Claude, and also unlocks the backlink marketplace, content agent workflows, and technical SEO fixes. Profound gates Claude behind Enterprise custom pricing; on Maintouch's Hypergrowth tier ($799/month) it's included on day one.

Custom plans include a dedicated forward deployed marketer, a content engineer, regular meetings with an AEO specialist, and a dedicated Slack channel. That's the direct substitute for the $2,000/month contractor Profound users end up hiring to act on their dashboards. Engine coverage scales by tier: Starter tracks ChatGPT, Google AI Overviews, and Perplexity; Scale adds Gemini; Hypergrowth and Custom include all five engines. The full Maintouch vs. Profound comparison breaks down the cost structures side by side.

The content engine compounds over time. Every time someone on your team edits a draft, the system diffs the changes and updates the knowledge base, brand voice, and blog rules automatically. Six months in, the output sounds like you wrote it.

Strategy, content, technical SEO, backlinks, citation tracking. One loop, no handoffs. If you want to see what that looks like on your actual data, shoot me a message at [email protected].

Final Thoughts on Profound's Place in the AI Visibility Category

Profound is a serious monitoring product. The funding behind it confirms the GEO category is real. But monitoring and doing the work are still two separate jobs on their self-serve tiers, and I've watched enough teams buy a monitoring tool, stare at the numbers for three months, and then ask who's going to do the work to know that gap has a cost.

If you want a system that closes that loop inside one place, shoot me a message at [email protected].

FAQ

How are Profound GEO visibility scores actually calculated?

Profound runs your target prompts across AI engines like ChatGPT, Perplexity, and Gemini, records whether your brand gets cited in each response, then applies a weighting layer that multiplies citation frequency by estimated prompt volume or strategic importance. Share of voice adds the competitive layer: if you're cited in 15% of responses and a competitor hits 40%, that gap is the signal worth acting on. Treat the output as directional intelligence for prioritization, not a precise conversion metric.

What is the relationship between SEO and AEO, and do I need two separate strategies?

They share the same foundation. AI engines run a web search under the hood before generating answers, so strong traditional rankings directly feed citation outcomes. Running two separate strategies is structurally broken. The brands getting cited in AI-generated answers are almost always the same ones with clean structured data, fresh content, and solid backlinks: the SEO work and the AEO work compound each other inside one system.

Profound GEO vs. Maintouch for a B2B startup that needs the work done, beyond the signal?

Profound is a monitoring and recommendations product: its self-serve tiers surface citation gaps and suggest content changes, but execution still happens in separate tools with a contractor or internal analyst doing the coordination. Maintouch closes that loop inside one system, strategy, content creation, technical SEO fixes, backlink procurement, and citation tracking across all five engines, with a dedicated strategist on weekly standing syncs included in every paying account. Independent reviewers have noted Profound users often hire an external contractor at roughly $2,000/month on top of their subscription to act on the dashboards; that layer is built into Maintouch at no additional cost.

How do fan-out queries work and why do they matter for getting cited in ChatGPT and Perplexity?

When someone submits a prompt to ChatGPT or Perplexity, the engine breaks it into sub-questions before pulling candidate pages through search, a process called query fan-out. Each sub-question gets its own retrieval pass, so a single user prompt can trigger five to ten separate ranking checks against your content. If your pages answer those sub-questions directly in self-contained passage-level blocks of 130 to 170 words, with the entity named inside the block, you show up across more of those retrieval passes and increase your citation share without publishing more pages.

Can I track Profound GEO metrics for free before committing to a paid plan?

Profound offers a free 7-day Trial covering ChatGPT, Gemini, and Google AI Overviews, after which the only path forward is a custom Enterprise conversation. Every Maintouch self-serve tier (Starter at $149/month, Scale at $399/month, Hypergrowth at $799/month) starts with a 5-day free trial. Claude coverage sits behind Profound's Enterprise tier and requires a custom pricing conversation; on Maintouch's Hypergrowth tier it's included from day one.

Does Profound integrate with tools like Ahrefs, Semrush, or my CMS?

Profound's Enterprise tier includes connectors for Tableau and Power BI for reporting output, and its Agent layer can chain tasks in a Zapier-style workflow builder. It doesn't push content or fixes directly into a CMS the way an execution system would. Acting on the gaps Profound surfaces still requires your existing content tools, a writer, and someone to coordinate the handoff.

How does citation drift affect my GEO strategy, and how fast does it happen?

Profound's own research puts citation drift at 40-60% monthly across major AI engines, meaning a large share of your tracked citations can change before your team responds. AI engines pull fresh content into their retrieval sets continuously, so a page that earns citations today can lose them within weeks if a competitor publishes a more current or better-structured answer. The practical implication: monitoring without a fast execution loop means you're chasing a moving target, not closing ground on one.

Is Profound GEO worth it for a small team without a dedicated analyst?

Probably not on the self-serve tiers. Independent reviewers consistently flag Profound's dashboard as data-heavy and not intuitive out of the box, and the product surfaces recommendations instead of executing them. Without someone who can live in the dashboards, interpret citation trends, and coordinate content execution in separate tools, you end up paying for signal you can't act on fast enough to matter.

What's the difference between GEO, AEO, and LLMO: are they the same thing?

Essentially, yes. They describe the same underlying practice: optimizing your content to appear in AI-generated answers from engines like ChatGPT, Perplexity, Gemini, and Claude. The industry hasn't agreed on a single term. Profound uses GEO; Maintouch uses AEO as the label. The mechanics are identical: structured data, passage-level content optimization, and strong backlink profiles that feed AI retrieval systems.

How do I know if my content is actually getting cited in AI answers, or just ranked in Google?

Google rankings and AI citations are related but not the same thing. A page can rank on page one and still be invisible in ChatGPT or Perplexity responses if its structured data is incomplete or its content isn't optimized at the passage level. The only way to know your citation status is to run prompts directly against each engine and record whether your brand appears in the response. That's exactly what AI visibility tracking tools like Profound and Maintouch's free tier do: they separate citation share from ranking position so you're measuring what actually matters for AI-driven discovery.

What happens to my GEO visibility if I stop publishing new content?

GEO isn't a one-time setup. It compounds when you keep feeding the system and decays when you stop.