Brand monitoring · last updated 2026-06-08
Evertune
AI brand-measurement platform from a team of ad-tech veterans, focused on how models represent brands across answers, not just whether a URL is cited.
- Category
- Brand monitoring
- Founded
- 2024
- HQ
- New York, NY
- Pricing model
- Contact sales
- Methodology transparency
- High
- Data exportability
- Yes
- Engines tracked
- 5 (ChatGPT Search, Perplexity, Claude, Gemini, Google AI Overviews)
- Website
- www.evertune.ai
Evertune was founded by alumni of The Trade Desk, and the ad-tech heritage shows in the methodology: rather than checking a handful of queries, Evertune samples model behavior across large prompt sets to estimate how often, and how favorably, a brand appears in generated answers. The unit of analysis is brand representation, not a single citation.
That makes Evertune a complement to, more than a substitute for, the per-page rank-trackers. A citation-share tool tells you which of your URLs got cited; Evertune tells you what the models tend to say about you in aggregate, including where you are recommended over competitors and where you are not.
Evertune is well funded for its stage (tracked on the investor landscape page). Evaluate it when the question is "how do the models talk about our brand," and pair it with a URL-level tracker like Profound or AthenaHQ when the question is "which of our pages is getting cited."
Standout strength
Measurement rigor from an ad-tech-veteran founding team: strong on statistical sampling of model behavior across many prompts, not single-query snapshots.
Honest limitations
- Brand-representation framing is distinct from per-page citation tracking; it answers a different question than a rank-tracker.
- Enterprise sales motion; less suited to self-serve mid-market evaluation.
Best fit for
Brand and insights teams who want a statistically defensible read on how models describe and recommend them, beyond URL-level citation counts.
Frequently asked questions
- Which AI engines does Evertune track?
- 5 as publicly stated by the vendor: ChatGPT Search, Perplexity, Claude, Gemini, Google AI Overviews. Engine coverage is the first thing to check against the engines your buyers actually use, because a citation you cannot see is one you cannot act on.
- How is Evertune priced?
- Contact sales. Pricing is not published. Expect a sales conversation before you see a number, which also means list-price comparison against other vendors is not possible from public sources.
- Can you export raw data from Evertune?
- Yes. Raw data can be exported, so you can run your own analysis and keep a record that survives leaving the platform.
- Who is Evertune best for?
- Brand and insights teams who want a statistically defensible read on how models describe and recommend them, beyond URL-level citation counts.
- What are the limitations of Evertune?
- Brand-representation framing is distinct from per-page citation tracking; it answers a different question than a rank-tracker. Enterprise sales motion; less suited to self-serve mid-market evaluation.
Funding & investors
Full investor landscape →Venture-backed · $19M disclosed
Seed · $4M
Led by Eniac Ventures; with NextView Ventures
Series A · $15M · 2025-08
Led by Felicis Ventures; with Eniac Ventures, NextView Ventures
Founded by alumni of The Trade Desk; measures brand representation across model outputs.