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Atlas/Profound
Vendor dossier / SEO / AEO

Profound

AI visibility and answer-engine optimization platform with agentic marketing workflows.

REVIEWED 23 SEPTEMBER 2026MarketingNO HANDS-ON BENCHMARK

What it is

Official-source notesSEO / AEOscaling

Profound combines AI visibility measurement with AI Marketer context and workflows. The current pricing page shows a free trial and enterprise packaging rather than a reliable universal self-service rate. [V1] [V2]

Documented means the statement is present in the cited material. Capability effectiveness, customer outcomes and security assurances have not been independently audited here.

Promoted use cases

  • Track brand representation in AI answers
  • Identify citation and content opportunities
  • Run context-grounded marketing workflows

AI-search tools observe a shifting answer environment. A mention, citation, ranking and customer conversion are different events. The useful comparison separates measurement coverage, diagnosis, content production and the ability to implement an approved change. An AEO dashboard is not a complete growth team, but it may supply essential evidence to one.

Pricing and buying model

Published commercial evidence

Free trial; Enterprise custom

Trial: 10 prompts run once on ChatGPT. Enterprise monitoring and AI Marketer credits are quoted.

Check current commercial source ↗

Budget for implementation, model and tool usage, data, human review and ongoing support. Credit units and outcome definitions differ between vendors. A missing numeric rate is marked unverified rather than replaced with an old third-party estimate.

Collaboration and governance

The page describes credit estimation and administration. Verify approval and publishing rights within the contracted workflows.

The relevant unit of control is permission to publish a change to website content. Inspect who can propose, approve, execute, interrupt and audit that action. Shared seats, shared content and a shared live agent session are different capabilities; require a demonstration of the one your process needs.

Evaluate memory correction, permission revocation and release control for updated instructions. An improvement loop should preserve the original evidence, proposed change, test results and named approver. A safety or security badge alone cannot establish those workflow properties.

Review and customer evidence

A September 2026 G2 reviewer describing agency work calls out substantial onboarding and a high price while still finding operational value. Other visible reviews praise visibility tracking and ask for clearer explanations of score changes. Individual agency and brand use cases differ; these accounts do not independently validate claimed traffic or pipeline lift.

Before relying on a testimonial, confirm the exact product, version, package, workload and baseline. Ask a relevant customer about setup effort, failed cases, ongoing manual work and support after launch. This dossier does not convert customer logos or vendor-hosted awards into independent proof.

Focused feature documentation

Focused documentation check · Sep 2026

Prompt measurement, agent analytics and agent-credit meter

Profound describes Answer Engine Insights as daily runs of structured prompts with captured answers, brand visibility, citations and sentiment. Its Pages view combines citation share and agent visits for owned URLs. That connects external AI answers to crawler interaction but does not establish that a visibility change caused incremental qualified demand. In a pilot, preserve the prompt set and measure downstream traffic and accepted pipeline alongside answer changes.

The current official pricing page offers a seven-day trial with 50 prompts run daily across three named answer engines, with limited AI Marketer credits. Enterprise prompt customization and ongoing coverage require a quote. Profound Agents use credits that vary with run complexity; the platform shows estimated credits before a run and actual use after it. Agency Growth is a separate self-service offer of 400 credits per client workspace monthly. Do not conflate monitoring prompts, agent executions and completed content.

Primary sources: Official pricing and trial scope ↗ · Official Answer Engine Insights documentation ↗ · Official Pages documentation ↗

Published documentation and public illustrations; account behaviour was not independently tested.

Visual source

Public Profound source page captured 22 September 2026
Profound · Public page captured 22 Sept 2026. Vendor presentation, not an authenticated product test. Open source ↗

Fit, limitations and proof requests

Editorial assessment

Profound should be evaluated both as a measurement system and as an execution layer. A visibility chart alone does not prove qualified demand or incremental revenue.

Priority question: How are prompts sampled and repeated, and how do we distinguish real visibility change from answer variability?

The evaluation owner should be the organic growth or content lead. Use qualified discovery and accepted editorial improvements as the business target. Judge the solution in its own stack role: a cloud runtime, a specialist production tool and a managed AI team can be complementary purchases.

Use-case evaluation plan

Visibility diagnosis with repeatable sampling

Define a buyer-question set before the pilot, segment it by intent and geography, and repeat observations across the engines in scope. Record mentions, citations and answer quality separately. Add neutral and competitor-oriented questions so the exercise does not reward a tool merely for tracking prompts already favorable to the brand.

Measure: coverage, answer variability, citation accuracy and useful diagnostic findings.

Evidence to an approved content change

Choose one material gap and ask the system to explain its source evidence. Request a proposed page revision with factual references, an editorial review and a publication boundary. A marketer should be able to reject the recommendation while preserving the underlying measurement and reasoning.

Measure: accepted recommendations, factual corrections and publishing effort.

Discovery to commercial contribution

Track meaningful website visits and qualified conversions where attribution is technically available, while acknowledging unobservable journeys. Compare the changed pages with similar unchanged pages and note concurrent campaigns. Do not call a short-term visibility movement a causal revenue result without evidence.

Measure: qualified visits, conversions, editorial cost and stability of observed improvement.

Detailed comparison

Read the detailed Nagent vs Profound guide for operating models, shared context, governance, cost, evidence gaps and a staged pilot.

Nagent vs Profound

Sources and evidence register

Nagent · Multiplayer AI for growth teamsResearch: 21–29 September 2026 · Public-source analysis, no hands-on benchmark · Sources & method