Features
Inside the Yolando platform
A simple overview of what each feature does, the pain it solves, and how teams use it to shape their presence in AI answers.
Solution
Pain Point
Use Cases
Solution
Pain Point
Use Cases
Topics and prompts
Yolando turns your real buyer questions into structured prompts that run across AI platforms (ChatGPT, Gemini, Perplexity, and Claude) every day.
Yolando then identifies which prompts you’re visible in, where you are invisible, how you’re being talked about by AI, and which competitors show up.
Topics group related prompts so you can see performance at a strategic level, while each prompt captures a specific question a buyer would ask.
Most teams have no clear view of how they show up in the actual questions buyers ask across AI platforms.
Even with scattered keyword lists and prompt ideas in spreadsheets and SEO tools, there is no single source of truth that reveals where you appear, are missing, or how you compare to competitors.
This makes it nearly impossible to answer basic questions like which topics you are winning in and which buyer queries require immediate attention.
A B2B SaaS company creates Topics such as Pricing, Security, Use Cases, and Integrations, then tracks prompts like “best project management tool for agencies” or “ProjectTool vs Asana for time tracking” to guide content.
An ecommerce brand sets up TOFU prompts such as “best sustainable skincare sets” and MOFU prompts such as “vitamin C serum for sensitive skin” to see how often they appear in AI responses.
A law firm defines Topics for Family Law, Real Estate, and Employment, then uses prompts like “employment lawyer in New York” to prioritize which practice area pages and guides to write first.
Citations
The Citations feature shows which domains and webpages AI platforms rely on when generating answers for your prompts – essentially, the web search sources used.
Yolando groups every cited domain into Owned (your website), Competitor, Earned (third party sites), or Social, and tracks how your citation share changes over time.
You can drill into any domain to see the exact URLs that are being cited, which topics they influence, and which platforms reference them most often.
Brands publish content but have no clear way to see which sources AI models actually cite when generating answers, leaving them blind to the material that shapes buyer perception.
Teams cannot tell whether their own content is influencing the narrative, nor can they identify which competitor pages, third party sites, or community threads are driving authority.
Without this visibility, both content strategy and outreach efforts rely on guesswork, generic media lists, or gut feel instead
A B2B SaaS company sees that a competitor’s feature comparison blog is repeatedly cited in AI answers for “best procurement automation tools,” so they create a stronger, more up to date comparison page and reach out to the same industry analyst blogs that AI is already citing.
A dental practice network identifies Reddit threads being referenced in AI responses and joins the conversation to clarify misconceptions and add expert guidance.
Reputation
Reputation in Yolando analyzes the tone and framing of your mentions across AI responses, turning them into a clear Reputation Score.
The platform surfaces recurring themes, such as praise for ease of use or criticism around pricing, and classifies them as positive or negative.
You can open any theme to see the original AI responses, so you understand the exact wording and context that shape how buyers perceive your brand.
Knowing that you are mentioned in AI responses is only half the battle. What also matters is how you are being framed: positively, negatively, or in ways that subtly push users toward competitors.
Old reviews, outdated articles, and legacy talking points can continue shaping AI narratives long after your product, pricing, or positioning has improved.
Without a clear view into the tone and themes behind these mentions, teams have no reliable way to prioritize which narratives to fix, amplify, or counteract across the AI ecosystem.
A telehealth provider learns that negative sentiment clusters around “long wait times” in AI responses, then launches a new response time guarantee, updates their site, and runs a review generation campaign to shift the narrative.
A fintech brand sees that AI regularly praises their “transparent pricing,” and decides to feature this strength more prominently in landing pages and sales decks.
A B2B software company finds recurring negative themes about “complex onboarding,” and responds with step by step onboarding guides, success stories, and support content designed to address that concern directly.
Recommendations
Recommendations turn all of Yolando’s insights into a prioritized list of content opportunities. For each recommendation, Yolando explains what happened, why it matters, and the details of the recommended action.
With one click, you can turn any recommendation into ready-to-publish content in your Brand Voice, so there is a direct path from insight to action.
Dashboards alone do not tell busy teams what actions are most important to drive improvements.
Content teams spend time guessing which topics to cover instead of focusing on the keywords and subjects that would move discoverability, citations, and sentiment the most.
Without a clear, ranked to do list, teams struggle to build momentum and demonstrate progress in AI visibility.
A logistics platform receives a High priority recommendation to write “Supply chain visibility solutions for mid market manufacturers” after Yolando detects that competitors dominate these prompts in ChatGPT and Gemini.
A legal tech company sees recommendations to cover new case types and jurisdictions where they are currently invisible, then spins up briefs directly from those items.
A small marketing team at a B2B startup simply uses the Recommendations tab as their quarterly content roadmap, working from the highest priority items down.
Content Hub
The Content Hub acts as a central library for every content piece created in Yolando. It shows each item’s title, status, creator, and last edited date, so you always know what is in ideation, in drafting, or ready for publishing.
Whether content starts from a Recommendation or from a blank brief, it is automatically stored here, making the hub the single source of truth for your AI driven content pipeline.
Content is often scattered across documents, email threads, and multiple tools, which makes it hard for managers to see what exists and what is coming next.
Teams struggle to answer basic questions like how many articles were created this month or which pieces are still waiting on review.
Finding the latest approved version of a piece is time consuming, and work is often duplicated because there is no central record.
A fintech company brand keeps all campaign landing pages, evergreen articles, and FAQ content in the Content Hub, so the head of marketing can filter by status and see what is in Draft versus Published.
A B2B software company uses the hub to manage content across multiple client workspaces, quickly checking which recommendations have already been turned into assets.
A law firm tracks articles for each city and practice area, then uses filters to quickly identify which guides to update when legislation changes.
Content Editor
The Content Editor is a collaborative, AI assisted writing workspace where teams can take content from outline to polished, publish ready copy.
Real time collaboration lets multiple teammates edit simultaneously, see each other’s cursors, and react to changes as they happen.
Built-in commenting allows users to leave notes, ask questions, give feedback, or start discussion threads directly on the text.
When you highlight any section, the editor offers AI powered rewrite, shorten, expand, and tone adjustment tools that follow your Brand Voice.
Rich formatting and block based editing make long form pieces easy to structure, while exports to HTML, Markdown, and text ensure smooth publishing into any CMS.
Writers often juggle several tools to draft, edit, share feedback, and prepare content for their CMS, which slows production and creates confusion.
Teams lack a consistent place to capture comments and suggestions, so important feedback gets lost in email or chat.
Generic AI writing tools are not grounded in the brand’s tone or internal knowledge, producing content that sounds off and requires heavy manual editing.
A fintech company drafts thought leadership articles in Yolando, invites legal to review in Suggestion mode, and then exports HTML directly into their CMS once changes are approved.
An agency copywriter highlights a section and asks the AI to “make this more product led” while preserving the client’s Brand Voice, then quickly iterates on the suggested options.
A consumer brand turns a long form article into multiple social posts inside the same editor, keeping all versions linked back to the original brief.
Competitor Tracking
Competitor Tracking lets you define tracked competitors, automatically capture variations of their brand names, and benchmark your core GEO metrics against them.
Yolando scrapes their public content to enrich your knowledge base and shows where each competitor is winning on discoverability, share of voice, citations, and sentiment.
With “view insights as,” you can flip the perspective and see the entire Insights section through a competitor’s eyes, revealing exactly where they appear strong and where they are weak.
Competitive research usually happens in one off decks or ad hoc searches and is rarely tied to how AI platforms actually talk about your market.
Teams know who their competitors are, but cannot quantify who is winning the AI front door in specific topics, prompts, or platforms.
New challengers may start appearing in AI answers long before they show up in internal reports, leaving you reactive instead of proactive.
A project management vendor tracks Asana, Monday, and ClickUp, then compares discoverability and share of voice for Integrations related prompts across ChatGPT and Perplexity.
A DTC coffee brand switches to “view insights as” a key competitor to see which prompts that competitor dominates and which pages drive their citation share.
A cybersecurity company notices a previously unknown startup appearing in AI responses, upgrades it from untracked to tracked, and begins monitoring its content strategy and momentum.
Brand Voice
Brand Voice in Yolando analyzes your existing website, then generates a detailed profile capturing tone, vocabulary, and stylistic rules which you can refine.
This profile is applied automatically whenever you generate content, so everything produced by Yolando feels like it was written by your team.
You can create multiple voices for different audiences, products, or channels and select the appropriate one at generation time, ensuring consistent but context aware messaging.
Generic AI content often feels flat, inconsistent, or off brand, forcing marketers to rewrite large sections before publishing.
Static brand voice documents live in shared drives but rarely translate directly into the prompts writers use day to day.
Agencies, freelancers, and new team members struggle to internalize subtle tone and phrasing rules, leading to content that is technically correct but does not sound like the brand.
A B2B fintech company creates a confident, data driven Brand Voice for long form content and a slightly lighter voice for social posts, then chooses the right option inside each brief.
An online therapy platform imports its style guide and product language, then uses Yolando to generate landing pages that match the tone of its existing site.
A marketplace business sets up separate voices for buyers and sellers, so educational content for each side feels tailored without breaking overall brand consistency.
Custom Artifacts
Custom Artifacts allows you to upload internal documents, spreadsheets, presentations, and links so Yolando can learn from your proprietary knowledge, not just what is on your public site.
These materials are indexed into your private RAG knowledge base and used to ground recommendations, answers, and generated content in accurate product, pricing, and messaging details.
By keeping this collection fresh, you ensure that Yolando always reflects your latest positioning and launches, even before search engines and AI crawlers have caught up.
Many of the most important details about a brand live in internal docs, not on the website, so AI tools often miss nuance around features, pricing models, or service levels.
Rebrands and product changes can take months to fully propagate across the web, leaving AI systems with outdated information.
Without a structured way to feed proprietary material into the engine, generated content tends to be generic or slightly inaccurate, creating more editing work for the team.
A SaaS company uploads product one pagers, integration specs, and sales decks so Yolando can generate feature pages, competitive comparisons, and release notes that mirror the latest reality.
A law firm adds internal FAQs and jurisdiction specific memos, enabling Yolando to create articles that match the firm’s real world processes and language instead of generic legal summaries.
An ecommerce brand uploads campaign briefs and historic landing pages so new content borrows proven positioning and complies with internal brand rules.
Prompt Manager
The Prompt Manager is the control center for every prompt that powers your insights. It provides a structured view of all prompts by topic, funnel stage, and branded or unbranded type, and lets you add new prompts individually, generate suggestions in bulk, or upload a CSV for large changes.
You can pause prompts to stop them from running while preserving historical data, or delete them entirely when they are no longer relevant, keeping your measurement set sharp and aligned with strategy.
Managing dozens or hundreds of prompts across AI platforms quickly becomes unmanageable when handled by hand or stored in ad hoc documents. As your product evolves, it is easy for your measurement set to lag behind, leaving you focused on outdated questions that no longer match how buyers search.
Without clear ownership and structure, teams hesitate to add or remove prompts because they fear breaking dashboards or losing valuable historical trends.
A B2B SaaS team bulk uploads a CSV of prompts that cover TOFU, MOFU, and BOFU questions for each key product line, then refines the list over time based on performance.
An agency maintains separate prompt collections for each client and uses the Prompt Manager to keep topics like Pricing, Integrations, and Industry Use Cases organized and consistent.
A consumer brand periodically generates new prompts related to emerging trends, such as “AI skin analysis” or “plastic free packaging,” and pauses legacy prompts that are no longer a strategic focus.
