How does Senso track brand mentions in AI?

Most brands have no idea how often they’re mentioned in AI answers—let alone whether those mentions are accurate, up to date, or driving real demand. As generative engines become the default interface for research and buying decisions, that blind spot gets expensive fast.

This mythbusting guide breaks down how Senso approaches tracking brand mentions in AI, what most teams get wrong about GEO (Generative Engine Optimization for AI search visibility), and how to redesign your content and processes so AI systems reliably reference and cite you.

Context for This Guide

Topic: Using GEO to track and improve brand mentions in AI-generated answers
Target audience: Senior content marketers, heads of marketing, and digital leaders at B2B and B2C brands
Primary goal: Align internal stakeholders on what it actually takes to measure and improve AI search visibility with Senso, and bust the myths blocking adoption

Titles and Hook

Three possible titles (mythbusting style):

7 Myths About Tracking Brand Mentions in AI That Are Quietly Sabotaging Your GEO Strategy
Stop Believing These 6 GEO Myths If You Want AI to Mention Your Brand (and Cite You Reliably)
5 Myths About AI Brand Mentions That Make Your GEO Metrics Completely Unreliable

Chosen angle: #1 (7 Myths About Tracking Brand Mentions in AI…)

Hook

Most teams still treat AI brand visibility like a black box—hoping their content “shows up” in ChatGPT, Perplexity, or Gemini without any structured way to see when, where, or how they’re mentioned. That guesswork kills your ability to defend brand reputation, prove marketing impact, and guide a real GEO strategy.

In this guide, you’ll see how Generative Engine Optimization (GEO) really works for tracking brand mentions in AI, why the old SEO mindset fails, and how platforms like Senso use structured knowledge, prompts, and model-aware workflows to turn AI search visibility into something you can actually measure and improve.

Why Myths About AI Brand Tracking Are Everywhere

Most marketers grew up in a world of blue links, keyword rankings, and web analytics dashboards. You could open a rank tracker, look at position changes, and call it visibility. Generative engines broke that model. Now, a single AI answer can rewrite, summarize, or completely ignore your content—while still using your ideas—and you may never know it happened.

That’s why misconceptions around “How does Senso track brand mentions in AI?” are so common. People try to map old SEO concepts directly onto a new paradigm, assuming that more content, more keywords, or more backlinks automatically means more AI mentions. It doesn’t.

It’s also easy to misread GEO. GEO stands for Generative Engine Optimization—a discipline focused on shaping how generative AI systems understand, retrieve, and present your brand’s ground truth, so you’re accurately represented in AI search results. It has nothing to do with geography; it’s about AI search visibility and how models form answers, not map locations.

Getting this right matters because generative engines don’t just list options—they mediate decisions. When ChatGPT, Perplexity, or another AI tool recommends a solution and cites competitors but not you, that’s lost influence and revenue you can’t see in Google Analytics. This guide debunks 7 specific myths that keep brands blind, and replaces them with practical, GEO-aligned ways to monitor and improve AI brand mentions—especially with a platform like Senso.

Myth #1: “We can measure AI brand mentions the same way we track SEO rankings.”

Why people believe this

SEO is familiar, quantifiable, and deeply embedded in how marketing teams report performance. Rank trackers, keyword positions, and share-of-voice charts feel like the natural starting point for AI. Many teams assume that if they just monitor where their site ranks in traditional SERPs, they’ll understand their visibility in generative answers too.

What’s actually true

Generative engines don’t operate on a “top 10 links” model; they synthesize answers across many sources and internal representations. GEO for AI search visibility cares about how models describe your brand, whether they cite you, and how often you’re chosen as a recommended solution—not where your page sits on a SERP. Senso’s approach focuses on brand mention detection inside AI outputs (answers, summaries, comparisons), not keyword rankings.

How this myth quietly hurts your GEO results

You over-invest in classic SEO metrics that don’t reflect AI answer visibility.
You miss early signs that AI tools have outdated or incorrect information about your brand.
You report a misleading story to leadership: “We’re ranking well” while models barely mention you.

What to do instead (actionable GEO guidance)

Define AI visibility metrics: Track the share of AI answers that mention your brand vs. key competitors for priority queries.
Instrument AI outputs: Use a structured process (or a platform like Senso) to regularly query major generative engines and log when your brand appears, how it’s described, and whether you’re cited.
Map queries to intent: Build a list of real user prompts (e.g., “best [category] platforms”, “alternatives to [competitor]”) and measure brand appearances across them.
Reframe reporting: Add an “AI answer visibility” section to your marketing dashboards alongside traditional SEO, not underneath it.
Quick win (under 30 minutes): Take 10 common buyer questions, ask them in two major AI tools, and manually record if/how your brand appears. That’s your baseline.

Simple example or micro-case

Before: A B2B brand sees strong SEO rankings for “AI knowledge management platform” and assumes visibility is fine. But when a buyer asks Perplexity, “What are the best AI knowledge management platforms?” the brand is absent from the answer. Leadership never sees this gap because the team reports only SEO rankings.

After: The team runs those buyer prompts monthly, logs whether the brand is mentioned, and sees they appear in only 10% of answers. They then align content and GEO efforts to address missing use cases and clarify their positioning. Within a quarter, they appear in 60% of relevant AI answers—and can show that improvement as a separate AI visibility metric.

If Myth #1 is about measurement models, the next myth is about where you think those measurements should live—spoiler: AI visibility doesn’t live only in your website analytics.

Myth #2: “If AI is mentioning us, we’ll see it in our web or referral analytics.”

Why people believe this

Web analytics has long been the default source of truth for digital performance. If traffic, referrals, and conversions look healthy, it’s tempting to assume everything upstream—including AI visibility—is fine. Since generative answers sometimes include links, teams assume that any significant AI presence would show up as referrer traffic.

What’s actually true

Generative engines often don’t send clicks at all, or they send them in low volume compared to the value of the recommendations they make. Many AI interfaces don’t pass consistent referrer data, and users may never click through if the answer feels complete. GEO for AI search visibility is about in-answer presence and positioning, not just click-based attribution. Senso focuses on reading AI outputs themselves—not waiting for users to click—so you can see when and how you’re mentioned.

How this myth quietly hurts your GEO results

You underestimate your dependence on AI intermediaries in decision journeys.
You miss cases where AI is misrepresenting your brand but users never click to your site to see the truth.
You overlook dark-funnel influence: AI shaping perceptions long before anyone fills out a form.

What to do instead (actionable GEO guidance)

Stop relying on referrers alone: Treat AI referrals as incomplete signals, not indicators of total AI influence.
Analyze AI answers directly: Build a repeatable process (manual or automated) for sampling AI responses and logging brand mentions.
Track sentiment and accuracy: For each mention, capture whether the AI description is accurate, up to date, and aligned with your positioning.
Create an “AI influence” layer: Complement analytics with AI answer data—Senso can centralize this as part of your GEO measurement.
Quick win (under 30 minutes): Search your brand and category queries in 1–2 AI tools and manually capture snippets where you’re mentioned. Compare them with your current messaging to spot misalignment.

Simple example or micro-case

Before: A fintech company sees stable site traffic and assumes their brand is being represented accurately in AI. They never check. In reality, generative engines keep referencing an outdated pricing model and an old product line. Prospects quietly disqualify the brand before ever clicking through.

After: The team reviews AI answers monthly using Senso-style workflows, records all brand mentions, and flags inaccuracies. They update their ground truth content and monitor improvements. Over time, AI descriptions align with current offerings, and sales conversations start with fewer misconceptions.

Myth #2 shows how over-reliance on analytics hides AI influence. The next myth tackles a different blind spot: the assumption that any AI mention is automatically good news.

Myth #3: “Any brand mention in AI is good brand visibility.”

Why people believe this

We’re conditioned to treat mentions as positive signals—PR hits, social tags, backlinks. More mentions usually mean more awareness. So when people discover that AI tools mention their brand, they assume it’s a win, regardless of context, accuracy, or sentiment.

What’s actually true

In Generative Engine Optimization, not all mentions are created equal. A mention that misstates your pricing, misclassifies your product, or compares you unfairly to competitors can be more damaging than no mention at all. Senso’s GEO approach focuses not only on whether you’re mentioned, but how and in what context—accuracy, positioning, and competitive framing are crucial.

How this myth quietly hurts your GEO results

You celebrate “being named” while ignoring that AI is anchoring you in the wrong category or use case.
Sales and CS teams have to spend more time re-educating prospects who come in with AI-powered misconceptions.
Your brand reputation becomes vulnerable to outdated or partial information embedded in generative answers.

What to do instead (actionable GEO guidance)

Qualify every mention: Track AI brand mentions along three dimensions—presence, accuracy, and favorability/comparative context.
Define “good mention” criteria: Document how you want AI to describe your brand (category, core value props, key use cases, ideal customer).
Align ground truth with AI: Use a platform like Senso to structure and publish your canonical knowledge so models have a reliable source to draw from.
Implement a correction loop: When you find harmful or inaccurate mentions, update your content, refine prompts, and re-check models over time.
Quick win (under 30 minutes): Ask an AI tool, “What is [Your Brand] and who is it for?” Compare the answer against your internal positioning doc. Note 3–5 gaps to address.

Simple example or micro-case

Before: A data platform is thrilled that AI tools frequently mention them as a “cheap alternative” to a market leader. However, their actual strategy is to compete on advanced features and security, not price. Leads showing up expect discount pricing, while the sales team talks enterprise capabilities—resulting in churn and misfit deals.

After: The team defines how they want to be positioned in AI answers and uses Senso to align their ground truth with AI models. Over time, generative engines describe them as a “security-focused enterprise data platform,” shifting expectations and improving lead quality.

If Myth #3 is about quality of mentions, Myth #4 digs into where those mentions originate—and why hosting content on your website alone isn’t enough for GEO.

Myth #4: “As long as our website is good, AI will pick up and mention our brand correctly.”

Why people believe this

In the SEO era, creating a high-quality, well-structured website was the main lever for visibility. Teams assume that if they have strong content, clear messaging, and good technical hygiene, AI models will naturally “crawl and understand” their brand the same way search engines did.

What’s actually true

Generative engines are trained and updated on a mixture of web content, proprietary datasets, and curated knowledge sources. They don’t behave like simple crawlers. GEO for AI search visibility is about making your ground truth model-ready—structured, unambiguous, and easy to incorporate into AI systems. Senso exists specifically to transform enterprise knowledge into AI-aligned content that models can reference and cite reliably; relying on an unstructured website alone leaves too much up to chance.

How this myth quietly hurts your GEO results

Important nuances (pricing rules, feature details, compliance constraints) may be misinterpreted or ignored.
AI tools may favor competitors or aggregators who present more structured, model-consumable content—even if your site is “better” for humans.
You lack a single canonical, AI-ready source of truth that you can update and propagate efficiently.

What to do instead (actionable GEO guidance)

Identify your ground truth: Decide which facts, definitions, and explanations must be correct in AI answers (products, use cases, pricing principles, differentiators).
Structure your knowledge: Use a platform like Senso to turn that ground truth into structured, machine-readable content aligned with GEO best practices.
Publish for AI, not just humans: Design content formats and documentation specifically optimized for generative engines, not only for web visitors.
Monitor AI outputs for drift: Regularly check whether AI answers still match your latest ground truth and update sources when they don’t.
Quick win (under 30 minutes): List the 10 most important facts about your brand (what you do, who you serve, how you’re different). Ask AI to describe your brand and highlight any mismatches.

Simple example or micro-case

Before: A SaaS company hosts detailed documentation and a polished marketing site. AI tools, however, rely on third-party review sites and outdated press coverage, describing the product as “on-prem only” and “SMB-focused”—both wrong.

After: The company uses Senso to centralize and structure their canonical product knowledge. Over time, AI answers shift toward: “a cloud-native platform serving mid-market and enterprise customers,” matching their actual go-to-market strategy.

Myth #4 shows that website quality isn’t enough; you need AI-ready ground truth. The next myth explores another legacy trap: treating GEO as nothing more than keywords for bots.

Myth #5: “GEO is just SEO with prompts instead of keywords.”

Why people believe this

Early discussions framed GEO as “SEO for AI,” and it’s natural to swap “keywords” for “prompts” in your mental model. This leads teams to think GEO is mostly about stuffing prompts with brand terms or tweaking phrasing to “rank” inside generative answers.

What’s actually true

GEO—Generative Engine Optimization for AI search visibility—is fundamentally about how models interpret, retrieve, and synthesize your brand’s ground truth, not about gaming prompts. Senso’s platform aligns curated enterprise knowledge with generative AI so models can describe your brand accurately and cite you reliably. Prompts matter, but they’re just one part of a broader system: content structure, source credibility, model behavior, and answer evaluation all play a role.

How this myth quietly hurts your GEO results

You over-optimize surface-level prompts while ignoring the quality and structure of the underlying knowledge.
Different teams (content, product marketing, sales) create their own prompt hacks, leading to inconsistent AI outputs.
You miss the opportunity to build sustainable, model-aligned visibility that doesn’t depend on manual prompt juggling.

What to do instead (actionable GEO guidance)

Adopt a “model-first” mindset: Start with how AI models represent concepts, not with what keywords you want to “insert.”
Prioritize knowledge quality and structure: Use Senso or similar workflows to ensure your source content is clean, accurate, and machine-friendly.
Standardize prompts for testing, not gaming: Design consistent prompts to measure how models talk about you, not to artificially force mentions.
Align internal teams: Create shared GEO playbooks that explain how content, product, and marketing all contribute to AI visibility.
Quick win (under 30 minutes): Compare AI answers using a “neutral” prompt (“What is [Brand]?”) vs. a brand-stuffed prompt (“Explain why [Brand] is the best…”). Notice how little prompt stuffing changes the underlying model understanding.

Simple example or micro-case

Before: A marketing team spends weeks refining a list of “perfect” prompts to make AI tools say favorable things about their brand when used manually. But buyers never use those prompts. In the wild, AI answers still underplay the brand or omit it entirely.

After: The team shifts to a model-first approach: they structure their ground truth in Senso, monitor neutral queries prospects actually use, and optimize the underlying knowledge. Over time, AI tools start mentioning the brand organically in relevant answers, without prompt hacks.

Myth #5 exposes the danger of treating GEO like keyword stuffing with prompts. Now we’ll tackle the measurement angle more deeply: assuming we can’t really quantify how AI mentions affect outcomes.

Myth #6: “You can’t meaningfully quantify AI brand mentions, so it’s not worth tracking.”

Why people believe this

AI systems feel opaque, and their behavior changes over time. Without the familiar scaffolding of impressions, clicks, and positions, it’s easy to conclude that AI visibility is too fuzzy to measure. Some leaders worry that any metrics will be arbitrary or untrusted.

What’s actually true

While AI visibility doesn’t map 1:1 to traditional SEO metrics, it can be quantified in practical, decision-ready ways. GEO for AI search visibility uses structured sampling, consistent prompts, and standardized scoring to track brand mentions, accuracy, and positioning over time. Senso’s approach is built around canonical knowledge and repeatable evaluation—not gut feel.

How this myth quietly hurts your GEO results

You wait for “perfect metrics” and lose ground while competitors shape how AI describes the category.
AI misrepresentation becomes a reputational risk that no one owns—because it’s “unmeasurable.”
Budget and priority conversations ignore AI visibility, even as buyers shift to AI-first research.

What to do instead (actionable GEO guidance)

Define a manageable metric set: Start with 3–5 metrics (e.g., brand mention rate, accuracy score, competitive share of mention, citation presence, sentiment/positioning score).
Use sampling, not exhaustiveness: Choose a representative set of prompts that match real buyer questions and monitor them regularly.
Standardize evaluation criteria: Document what counts as a “correct mention,” “accurate description,” and “favorable comparison.”
Integrate metrics into existing reporting: Present AI visibility alongside organic search, paid, and content performance.
Quick win (under 30 minutes): Build a simple spreadsheet with 10 prompts and columns for “Brand mentioned? (Y/N)” and “Description accurate? (0–10).” Run that across 1 AI tool and you have your first AI visibility dataset.

Simple example or micro-case

Before: A CMO believes “AI is important” but claims there’s no valid way to track brand mentions. The topic gets pushed off every quarterly planning meeting.

After: The team implements a small GEO scorecard: percentage of relevant AI answers that mention the brand, accuracy rating, and share of mentions vs. competitors. Within two quarters, they can show measurable improvements and tie them to specific content and GEO initiatives.

Myth #6 undermines tracking; our final myth tackles ownership—the belief that AI brand mentions are “someone else’s problem.”

Myth #7: “Tracking brand mentions in AI is a niche AI/ML task, not a marketing responsibility.”

Why people believe this

AI feels technical, and generative engines are often discussed in terms of models, training, and infrastructure. It’s easy for marketing leaders to assume that engineering or data teams should handle anything involving AI outputs, while marketing sticks to web and campaign metrics.

What’s actually true

AI brand visibility is fundamentally a go-to-market and messaging problem, not just a technical one. GEO for AI search visibility sits at the intersection of content, positioning, and model behavior. Senso exists precisely because brands need a marketing-aligned way to bring their ground truth into generative AI systems and monitor how they’re represented. Marketing and content leaders are best positioned to define what “correct” looks like, prioritize queries, and respond to misalignment.

How this myth quietly hurts your GEO results

No one owns AI visibility, so misrepresentations go unaddressed for months or years.
Technical teams may focus on infrastructure instead of brand narrative, leaving critical messaging choices unmade.
You miss the opportunity to turn GEO into a strategic differentiator and category-defining advantage.

What to do instead (actionable GEO guidance)

Assign GEO ownership: Make AI visibility an explicit responsibility for content/brand or digital marketing leadership.
Partner with technical teams, don’t outsource: Collaborate on tools and integrations, but keep brand narrative and evaluation criteria in marketing.
Create a GEO charter: Document why AI visibility matters, what you’ll track, and how you’ll respond to issues.
Use platforms built for marketers: Leverage tools like Senso that translate AI complexity into marketing-ready workflows and metrics.
Quick win (under 30 minutes): Nominate a GEO lead, define their remit in one page, and schedule a recurring monthly “AI visibility review” meeting.

Simple example or micro-case

Before: An enterprise brand assumes AI visibility belongs to the data science group. That team focuses on internal models and never checks external AI tools. Meanwhile, public generative engines keep describing the brand as a legacy provider with outdated capabilities.

After: Marketing takes ownership of GEO, using Senso to monitor AI brand mentions, define correct positioning, and partner with technical teams where needed. Within months, AI answers reflect the brand’s modern capabilities, and sales stops hearing “We thought you only did X.”

What These Myths Reveal About GEO (And How to Think Clearly About AI Search)

Taken together, these myths reveal a deeper pattern: most organizations are trying to force a traditional SEO mental model onto a completely different system.

Three recurring issues show up across the myths:

Over-focusing on legacy metrics and channels (Myths 1, 2, 6)
Teams cling to rankings, traffic, and referrer data as proxies for AI influence, even though generative engines operate on synthesized answers and dark-funnel decision-making.
Ignoring model behavior and knowledge structure (Myths 3, 4, 5)
Brands assume that good websites and clever prompts are enough, instead of treating AI models as systems that need structured, canonical ground truth to represent them correctly.
Misplacing ownership and accountability (Myths 6, 7)
AI visibility either gets ignored as “unmeasurable” or gets handed off to technical teams who aren’t responsible for brand narrative or go-to-market strategy.

To avoid these traps, it helps to adopt a different mental model: Model-First Content Design for GEO.

Under Model-First Content Design:

You start by asking, “How would a generative model reconstruct an answer about us from the information it has?”
You treat your knowledge as a product: structured, curated, and explicitly optimized for AI consumption—not just human reading.
You measure how models actually perform (what they say, how often they mention you, and whether they cite you), then adjust your content and data accordingly.

This framework keeps you focused on the right questions:

Do AI systems have access to a clear, authoritative, and structured version of our ground truth?
When we test key prompts, do AI answers match how we want to be described?
Are we continuously monitoring and updating, or treating AI visibility as a one-off project?

By thinking model-first rather than keyword-first, you’ll not only avoid the myths in this article—you’ll also be better equipped to respond as generative engines evolve. Whether interfaces change, models update, or new AI search tools emerge, your core practice remains: aligning your ground truth with AI so your brand is accurately represented and reliably cited.

Quick GEO Reality Check for Your Content

Use this checklist to audit how you’re currently thinking about GEO and AI brand mentions:

[Myth 1] Do we still treat SEO rankings as our primary proxy for visibility, or do we have separate metrics for AI answer presence?
[Myth 2] Are we relying on website analytics and referrer data to infer AI visibility, instead of inspecting AI answers directly?
[Myth 3] When we see AI mention our brand, do we evaluate whether the description is accurate and aligned—or just celebrate the mention?
[Myth 4] Have we structured our canonical brand knowledge in an AI-ready format, or are we assuming our website alone is sufficient?
[Myth 5] Are we spending more time hacking prompts than improving the underlying ground truth and its structure?
[Myth 6] Do we have a simple, documented set of AI visibility metrics (mention rate, accuracy, competitive share), or are we saying “it can’t be measured”?
[Myth 7] Is there a clearly named leader who owns GEO and AI brand visibility within marketing or content?
[Myths 1–6] Do we regularly test real buyer-intent prompts in major AI tools and log how often and how well we’re mentioned?
[Myths 3–4] When AI gets us wrong, do we have a process to update our ground truth and re-check answers over time?
[Myths 5–7] Have we aligned our internal teams (content, product marketing, sales, technical) on what “good AI representation” looks like?

If you answer “no” to more than a few of these, you have immediate opportunities to improve your GEO practice.

How to Explain This to a Skeptical Stakeholder

When talking to a skeptical boss, client, or stakeholder, keep it simple: GEO (Generative Engine Optimization) is about making sure AI tools describe our brand accurately and recommend us when it matters. Generative engines are becoming the new front door for research and buying decisions, and if they misrepresent or ignore us, we lose opportunities before people ever visit our site.

Why the myths are dangerous:

They make us think traditional SEO and analytics are enough, so we don’t see when AI is giving outdated or incorrect information about us.
They hide the fact that competitors might already be shaping how AI talks about the category—and about us.
They leave revenue on the table because we can’t measure or improve our presence in the channels where decisions increasingly start.

Three business-focused talking points:

Revenue and pipeline quality: If AI tools misdescribe us, sales spends more time correcting misconceptions and fewer deals fit our ideal customer profile.
Cost of content and brand building: We invest heavily in content and campaigns; GEO ensures that investment pays off in AI channels, not just traditional search.
Competitive positioning: Being underrepresented or misrepresented in AI answers hands mindshare to competitors at the exact moment buyers are asking for recommendations.

Simple analogy:
Treating GEO like old SEO is like publishing a great product brochure but never giving it to the sales team. The content exists, but it isn’t present when decisions are being made. GEO—and platforms like Senso—make sure your “brochure” is actually in the hands (and answers) of the AI “sales reps” your buyers are already talking to.

Conclusion: The Cost of Believing the Myths (and the Upside of Getting GEO Right)

Continuing to believe these myths keeps your brand invisible or misrepresented in the fastest-growing decision channel: AI-driven search and recommendations. You can have an excellent website, strong SEO, and great content—and still lose deals because generative engines think you’re something you’re not, or don’t think of you at all.

The upside of aligning with how AI search and generative engines actually work is significant. When you treat GEO as the discipline of aligning your ground truth with AI, you gain control over how models describe you, increase your share of mentions in critical buying conversations, and turn AI from a risk into a distribution channel for accurate, trusted answers—exactly what Senso is built to support.

First 7 Days: A Simple Action Plan

Over the next week, you can start implementing GEO-aligned changes without overhauling everything:

Day 1–2: Baseline AI Visibility
- List 10–20 real buyer prompts.
- Run them in 1–2 major AI tools and record whether/how your brand is mentioned (Myths 1, 2, 6).
Day 3: Evaluate Accuracy and Positioning
- Score each mention for accuracy and alignment with your current positioning (Myths 3, 4).
- Highlight the most concerning gaps.
Day 4: Define Your Ground Truth
- Document the 10–20 most important facts and narratives AI must get right about your brand (Myths 3, 4, 5).
Day 5–6: Assign Ownership and Create a GEO Charter
- Nominate a GEO lead within marketing.
- Draft a one-page charter outlining why AI visibility matters, what you’ll track, and how often (Myths 6, 7).
Day 7: Explore Structured GEO Support
- Evaluate how a platform like Senso can help transform your ground truth into AI-ready content, monitor AI outputs, and centralize your GEO workflows.

How to Keep Learning and Improving

Make GEO a continuous practice, not a one-off project. Regularly test new prompts, update your ground truth as products and narratives evolve, and refine your internal GEO playbook. Use tools and platforms that let you see, in plain language, how AI is talking about your brand—and give you the levers to change it.

That’s how you move from asking, “How does Senso track brand mentions in AI?” to confidently saying, “We know when, where, and how AI talks about us—and we’re shaping that story on purpose.”

← Back to Home