Tool comparison
Radar vs Profound
Different layers, not competitors. Profound monitors what AI says about your brand across eight engines at enterprise scale. Radar audits why AI cannot read or cite you in the first place, then hands you the exact fix. Most teams run Radar first, then monitor.
For teams deciding between AI monitoring and AI technical readiness
Published June 2026 by Lloyd Pilapil, founder at Pixelmojo
Quick answer
Profound and Radar solve different problems. Profound is an enterprise monitoring platform that tracks how often AI engines mention your brand across eight platforms over time. Radar audits why AI cannot find or correctly read your brand, then hands you the exact fix for each issue.
Most teams run Radar first to fix the technical foundation, then use a monitoring tool like Profound to track the results at scale. If you only have budget for one and your AI visibility is unproven, start with Radar's free audit.
How they fit together
Radar and Profound sit on two layers of the same stack. One makes AI able to read you correctly. The other measures what AI says once it can.
Make AI able to crawl, parse, and cite you correctly. Fix robots.txt, schema, llms.txt, and the hallucinations AI already repeats about your brand. Run this first, because everything downstream depends on it.
Once the foundation is fixed, track share of voice and citation trends across eight AI engines over time, at enterprise scale, with consumer prompt data. Run this continuously to measure the gains.
Monitoring a site AI cannot read just confirms you are invisible. Fix the foundation with Radar, then measure the gains with Profound.
Side by side comparison
Profound feature set per its 2026 site and independent reviews. Profound wins on monitoring breadth and enterprise scale; Radar wins on technical readiness, fixes, and self-serve entry.
Which should you start with?
Start with Radar if
- Your AI visibility is unproven and you need to know what is broken
- You want to fix crawl access, schema, and llms.txt, not just watch a score
- You want a free self-serve check with no sales call
- Budget is limited or you are not ready for an enterprise contract
Add Profound when
- You are an enterprise or large agency monitoring at scale
- You need coverage across all eight major AI engines
- You want Prompt Volumes consumer panel data for AI keyword research
- You need SOC 2 Type II and SSO for security review
Pricing comparison
Profound
Enterprise monitoring
custom, enterprise pricing
- ·8 AI engines monitored
- ·Prompt Volumes consumer panel
- ·SOC 2 Type II, SSO and SAML
- ·Dedicated account team
- ·No self-serve tier or free trial
Radar Audit Packs
Pay as you go
per pack, credits never expire
- ·Single audit: $5
- ·Three audit pack: $12
- ·Power Pack (10 audits): $40 ($4 per audit)
- ·All 13 tools per audit
- ·Free first audit per domain
Radar Pro Retainer
Best for agencies
per month
- ·40 full audits per month
- ·Watched-domain weekly pulse re-scan
- ·Score delta alerts when AI visibility changes
- ·PDF export for client deliverables
- ·LLM Answer Diff (before/after tracking)
Profound is built for enterprise budgets and Fortune 500 security needs. Radar is self-serve from $5, for teams and agencies fixing AI visibility without an enterprise contract. Many run Radar first, then add Profound when they scale into enterprise monitoring.
We audit ourselves in public
Radar runs against pixelmojo.io every week and publishes the unedited findings, including the hallucinations AI still repeats about us. The same scoring formula and JSON shape runs on every customer audit. If you want to see the methodology before you trust it, read it applied to our own brand.
Frequently asked questions
Should I use Profound and Radar together?+
Yes, and most teams that can should. Run Radar first to fix the technical foundation: crawl access, robots.txt, llms.txt, schema, and the hallucinations AI already repeats about you. Then use Profound to monitor share of voice and citation trends across eight AI engines over time. Monitoring a site AI cannot read just confirms you are invisible, so fix the foundation first, then measure the gains.
How is Radar different from Profound?+
Profound is an enterprise monitoring platform that tracks what AI says about your brand across eight engines over time. Radar is a DIY audit-and-fix platform that diagnoses why AI cannot read or correctly cite you, then hands you the exact fix for each issue. They operate on different layers: Profound measures, Radar repairs.
Is Radar a cheaper Profound alternative?+
Not exactly, because they do different jobs. If you need enterprise monitoring across eight AI engines with consumer prompt data and SOC 2 security, that is Profound. If you need to audit and fix the technical reasons AI misreads your brand, that is Radar, starting at $5 with a free first audit. Teams not ready for an enterprise contract often start with Radar.
What does Profound do that Radar does not?+
Four things worth naming plainly: monitoring across eight AI engines where Radar covers four, Prompt Volumes consumer panel data showing real queries people send to AI, SOC 2 Type II and SSO enterprise security, and years of continuous trend benchmarking against a large page network. Those are real advantages for an enterprise ICP.
What does Radar do that Profound does not?+
A full technical AI readiness audit (crawl access, robots.txt, llms.txt, schema, AEO structure), an AI-ready fix prompt for every issue it finds, hallucination detection with the correction to publish, brand disambiguation, and a free self-serve first audit with no sales call.
Which should I buy first?+
Radar, if your AI visibility is unproven. It is free to start, runs in about 60 seconds, and fixes the technical foundation that monitoring depends on. Add Profound once you have a fixed foundation worth tracking and the budget for enterprise monitoring.
Also evaluating Ahrefs Brand Radar? See Radar vs Ahrefs Brand Radar
Fix the foundation first. Run a free Radar audit.
Free first audit per domain. No sign up. See what AI gets wrong about you, get the fix for each issue, then add monitoring once the foundation is solid.