FoundNow vs Profound

An enterprise AI-search monitoring platform focused on large brands - answer-engine impressions, agents and analytics at enterprise scale.

FoundNow is an AI-visibility product built for 2-10 person local marketing agencies: sample the assistants your clients' customers actually ask, hand them a white-label report, and fix the local data layer the answers read. Here is the honest, side-by-side picture (competitor data from their own materials as of 2026-09-30 - always verify current pricing before you buy).

Side by side

 FoundNowProfound
Engine coverageSampled through each engine's public API, with the exact engines and model versions used listed inside every report; Google AI Mode honestly marked as not covered until a compliant method existsMulti-engine enterprise monitoring; the exact surface list and methodology are shared in their sales process - not published as a public pricing-page table (qualitative - verify on their site)
Price per client locationFrom $49/month for 1 location down to $11.20 per location at 40 (Starter/Growth/Agency/Scale) - white-label included on every tierEnterprise pricing, published on request only - no per-location unit pricing to compare (qualitative - verify on their site)
White-labelIncluded on every tier - reports, PDF and dashboard carry your brand, never oursEnterprise/brand-oriented; not positioned as a per-agency white-label deliverable for local client rosters (qualitative - verify on their site)
One-time reportYes - a deep audit (20+ core buyer questions, 5+ samples per question per engine) with a competitor gap and fix list, fully white-labeledNo self-serve one-time report (qualitative - verify on their site)
Local data-layer fixesThe product ships it: a 5-point data-layer checklist (Google/Yelp/Bing/Apple + NAP) plus ready-to-paste LocalBusiness schema, FAQ and service page copy, llms.txtNot a local data-layer product - enterprise analytics, not per-location fix execution for local businesses (qualitative - verify on their site)

What actually differs, in plain words

See it on a real business

The one-time scan samples an AI assistant with buyer questions about a location and shows mention rates with 95% confidence intervals - about a minute of waiting, and the full price is credited toward an audit. The methodology page explains exactly how the numbers are produced.