Mentions gives a team a clear picture of its AI presence and a tidy board of what to do about it. MentionOS exists for the step after the board: the Agent does the work itself, and the backlog stops waiting for someone's free afternoon.
MentionOS vs Mentions, side by side
| Dimension |  MentionOS | MMentions |
|---|---|---|
| The product in one line | The operating Agent for AEO: it reads, decides, does the work and proves it | AI mention tracking with sentiment, competitor comparison and a recommendations board |
| Engines | ChatGPT, Claude, Gemini, Google AI and Perplexity | Eight listed, including ChatGPT, Perplexity, Claude, Grok, Gemini, DeepSeek, Google's AI Overview and Llama |
| What a finding becomes | A proposal with the finished work attached, shipped on your approval | A card on the Insights Board for your team to prioritise and execute |
| Content and product copy | Written by the Agent; published through Shopify, WooCommerce, Wix, WordPress, WordPress.com, Webflow or Framer; weak product copy rewritten | Recommendations, with execution owned by the user |
| Technical conditions | Issues flagged with the fix proposed as an approvable move | Crawler analytics and tracking views |
| Reach | Multi-language response analysis across countries | Multi-language and country analysis as well |
| Accountability | Receipts on every action; a daily brief on what changed and why | The board tracks what your team marked done |
| Oversight model | Propose first, approve or decline, narrow revocable standing authority | Users decide what to execute |
| Where you work with it | One conversation in the app, Slack, iMessage and email | Web platform, with seats for the whole team |
| Built for | Brands that want the AEO function run for them | Individuals, teams and agencies running the work themselves |
Competitor details are indicative and current as of July 2026.
MentionOS vs Mentions: the full comparison
First, the names
Buyers genuinely mix these products up, and search engines sometimes do too, so here is the plain version. MentionOS is at mentionos.ai; the product is an autonomous Agent that runs Answer Engine Optimisation for a brand. Mentions is at mentions.so; the product tracks AI mentions and organises improvement recommendations for a team to act on. Neither company is affiliated with the other. If you arrived here comparing the two, the honest one-line separator is this: both will tell you where you stand in AI answers, and only one of them then does the work.
What Mentions does well
Mentions covers a lot of tracking ground. Eight engines is wide coverage, Llama and DeepSeek included, sentiment sits alongside visibility, competitor comparison is built in, responses can be analysed across languages and countries, and the Insights Board is an organised way to turn findings into a workable backlog. Unlimited seats across the product makes it easy to put the whole team in front of the same picture. As a tracking-and-triage layer, it is a coherent product.
A backlog is a promise. The Agent is how it gets kept.
The Insights Board is the most honest feature in this comparison, because it names the true bottleneck: a prioritised list of recommendations still needs hands. Every card on a board like that is work waiting for a writer, an editor, a developer or a founder's weekend. In teams with spare capacity, the board empties. In most brands, it grows.
MentionOS was built for the growing kind. The Agent generates its own findings from the questions your buyers ask, then closes them itself: the article drafted and published to your domain, the product copy rewritten, the technical fix proposed with specifics, each move sent for your approval and each action leaving a receipt. The daily brief reads like a colleague's update, what changed, what I did, why, and Search Console with Analytics, connected for every customer, shows whether the work moved anything. Approvals over time can grant the Agent narrow standing authority, revocable in one action, and its toolset extends through scoped connections, APIs, MCP servers, and outreach setup via connected tools such as Instantly where sending stays yours. The difference in one sentence: one product manages the to-do list, and the other is the reason the list shrinks. What the shipped work looks like is in how to get ChatGPT to recommend your brand.
Why choose MentionOS over Mentions
Findings close instead of queueing
The Agent's findings arrive with the work done and ship on your yes. Nothing waits on a card for capacity your team does not have.
AEO stops being everyone's side job
One Agent holds the function, works its own schedule, and comes to you for decisions only.
Published where the authority accrues
Approved content lands on your own site through the platform you already run.
Receipts and real outcome data
Every action keeps its chain, and briefs stand next to Search Console and Analytics numbers rather than on their own word.
Approvals from any channel
App, Slack, iMessage or email, one continuous thread. A yes from your phone ships the work.
FAQs
Straight answers on MentionOS vs Mentions, no fine print.
Are MentionOS and mentions.so the same company?
No. The names are close and the space overlaps, but they are unrelated companies with different products. MentionOS (mentionos.ai) is the autonomous AEO agent that does the visibility work itself. Mentions (mentions.so) tracks AI mentions and organises recommendations for your team to execute.
Both products track AI mentions. Where do they part?
At the moment a finding needs hands. Mentions places it on the Insights Board for your team to prioritise and execute. MentionOS assigns it to the Agent, which writes, publishes on your approval, verifies the publish and reports the movement, keeping a receipt at each step.
Which covers more engines?
Mentions lists eight, including Llama, DeepSeek and Grok. MentionOS reads five: ChatGPT, Claude, Gemini, Google AI and Perplexity. If breadth of tracking is the deciding factor, count that fairly; our position is that the deciding factor is who does the work the tracking calls for.
Which should a small team with no spare hours choose?
That constraint is the choice. A recommendations board assumes hours to execute; a team without them accumulates cards. MentionOS was built so the hours are the Agent's, and the human contribution shrinks to reading proposals and saying yes or no.