LLM Pulse review: pricing, features & alternatives

In a category defined by sales calls and self-issued #1 badges, LLM Pulse publishes six tiers (€49 to €999), gives every plan unlimited seats, and includes its MCP server even during the 14-day trial. Behind it are three Barcelona founders — GEO consultant Esteve Castells, TheTool founder Daniel Peris (previously acquired), and engineer Adrian Rojas — bootstrapped and profitable since launch in July 2025, with Softonic, Adevinta, and Casa Batlló among named customers.

Feature breadth outruns the price: sentiment, citations, share of voice, a GEO writer, owned-media tracking across YouTube/Reddit/social, AI traffic analytics, ChatGPT Shopping and AI-ads tracking, plus CSV/PDF exports and a Data Studio connector.

Cadence is the big one: default plans run prompts weekly (Mondays), so a visibility drop can sit invisible for most of a week. Daily variants exist but cost more and carry no trial. Engine coverage is five on every plan — ChatGPT, Perplexity, Gemini, AI Mode, AI Overviews — with Claude, Copilot, Grok, DeepSeek, and Meta AI all Enterprise add-ons, which stings for Claude-heavy B2B categories. The headline prices also assume annual billing; month-to-month is higher.

And the evidence base is thin: essentially one verified G2 review as of mid-2026, with the rest of the coverage being SEO-blog writeups — including LLM Pulse's own blog ranking itself #1, and at least one 'review' written by a direct competitor. The positive narrative is probably deserved, but it currently rests on the founders' own storytelling.

Small teams and agencies that want the whole team in a transparent, capable tracker without per-seat math — at €49 with a 14-day trial, it's one of the safest experiments in the category, with zero VC-collapse risk.

Teams that need same-day drop detection, Claude coverage without Enterprise pricing, or SOC 2 compliance should size up — those are architecture decisions, not settings.

Every row below is a capability we already listed for LLM Pulse. It is the published feature set for this page, not a guess at an unpublished demo. Compare it with the Promptwatch checklist that follows.

On this listing, LLM Pulse is a AI visibility tracker for Small teams and agencies that want transparent self-serve pricing and whole-team access without seat fees — at weekly cadence.. What we sourced here: 5 engines on all plans: ChatGPT, Perplexity, Gemini, AI Mode, AI Overviews; Sentiment, citations, share of voice, GEO Writer, AI traffic analytics; Owned-media tracking (YouTube, Reddit, social), ChatGPT Shopping and AI ads tracking; Unlimited seats and MCP server on every plan; REST API from €299.

If you buy LLM Pulse for the job above, plan a second tool (or Promptwatch) for the layers this listing does not document. Still missing here: AI crawler logs (Agent Analytics), crawl-to-citation path, bot errors; Visitor analytics: AI-referred sessions and conversions; Content Agents that plan, write, and publish GEO pages to a CMS with a review inbox; Citation analytics at page, domain, Reddit, YouTube, and offsite level; Prompt volumes, difficulty, query fan-outs, personas, city-level geo; Prompt and citation trends (what changed between checks); Agent Chat, Unified Actions, MCP server / REST API on paid plans. Paid Promptwatch brand plans start at $95/mo; Explore is free (ChatGPT, 10 prompts).

LLM Pulse's public pages (and this listing) describe a narrower job than Promptwatch. Most rivals answer whether you were mentioned. Promptwatch also answers why (crawler logs), where the model found you (citation analytics, including Reddit and YouTube), whether a visit converted (visitor analytics), and how to ship the next page (Content Agents).

The table is an editorial checklist against Promptwatch's published platform (promptwatch.com/llms.txt, 2026-08-23). It is not a hidden feature list for this vendor. 'Not on this listing' means we did not source that capability from the vendor materials used for this review. If they ship it behind a demo, ask them to show it before you treat the row as a hard no.