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#FAQ
Everything you need to know
Everything you need to know about how Rankad works, what it tracks, and how it helps your brand win visibility inside AI search.
#FAQ
Everything you need to know
Everything you need to know about how Rankad works, what it tracks, and how it helps your brand win visibility inside AI search.
#FAQ
Everything you need to know
Everything you need to know about how Rankad works, what it tracks, and how it helps your brand win visibility inside AI search.
Everything about AI Search Fundamentals
What is AI search optimization?
AI search optimization is the process of making your brand visible, trusted, and recommended inside AI assistants like ChatGPT, Gemini, and other large language models. Instead of ranking blue links, AI search focuses on how models understand entities, trust signals, citations, and brand relevance when answering real user questions.
What is AI search optimization?
AI search optimization is the process of making your brand visible, trusted, and recommended inside AI assistants like ChatGPT, Gemini, and other large language models. Instead of ranking blue links, AI search focuses on how models understand entities, trust signals, citations, and brand relevance when answering real user questions.
How is AI search different from traditional SEO?
Traditional SEO optimizes for search engines like Google and Bing. AI search optimization focuses on how AI models interpret, select, and recommend brands in conversational answers. Key differences: - SEO ranks pages - AI search recommends brands - SEO is keyword driven - AI search is intent and trust driven Rankad is built specifically for AI driven search behavior.
How is AI search different from traditional SEO?
Traditional SEO optimizes for search engines like Google and Bing. AI search optimization focuses on how AI models interpret, select, and recommend brands in conversational answers. Key differences: - SEO ranks pages - AI search recommends brands - SEO is keyword driven - AI search is intent and trust driven Rankad is built specifically for AI driven search behavior.
Can Rankad work alongside traditional SEO?
Yes. Rankad complements traditional SEO. SEO builds discoverability. AI optimization builds recommendation power. Together, they create full search dominance across both engines and AI assistants.
Can Rankad work alongside traditional SEO?
Yes. Rankad complements traditional SEO. SEO builds discoverability. AI optimization builds recommendation power. Together, they create full search dominance across both engines and AI assistants.
Do you offer packages or custom quotes?
Both. We have a few starter packages to keep things simple, but we also offer custom quotes for projects with unique needs. Just tell us what you're planning — we’ll work around it.
Do you offer packages or custom quotes?
Both. We have a few starter packages to keep things simple, but we also offer custom quotes for projects with unique needs. Just tell us what you're planning — we’ll work around it.
What is AIO/AEO/GEO/AI SEO?
AIO, AEO, GEO and AI SEO are different terms that describe how brands optimize visibility inside AI-driven search and answer engines like ChatGPT and Gemini. AIO (Artificial Intelligence Optimization) focuses on how AI models understand, trust and recommend brands, products and services. AEO (Answer Engine Optimization) focuses on optimizing content so AI assistants can directly use it when generating answers. GEO (Generative Engine Optimization) focuses on influencing how generative AI systems select sources, entities and citations when composing responses. AI SEO is the umbrella term that combines traditional SEO with AIO, AEO and GEO to ensure visibility across both search engines and AI assistants. Together, these disciplines ensure your brand is not only indexed, but actively chosen and recommended by AI at the moment of intent.
What is AIO/AEO/GEO/AI SEO?
AIO, AEO, GEO and AI SEO are different terms that describe how brands optimize visibility inside AI-driven search and answer engines like ChatGPT and Gemini. AIO (Artificial Intelligence Optimization) focuses on how AI models understand, trust and recommend brands, products and services. AEO (Answer Engine Optimization) focuses on optimizing content so AI assistants can directly use it when generating answers. GEO (Generative Engine Optimization) focuses on influencing how generative AI systems select sources, entities and citations when composing responses. AI SEO is the umbrella term that combines traditional SEO with AIO, AEO and GEO to ensure visibility across both search engines and AI assistants. Together, these disciplines ensure your brand is not only indexed, but actively chosen and recommended by AI at the moment of intent.
Can you work with our existing dev or marketing team?
Yes, absolutely. We’re happy to collaborate with your team — whether it's development, content, or marketing. Clear communication and teamwork always lead to better results.
Can you work with our existing dev or marketing team?
Yes, absolutely. We’re happy to collaborate with your team — whether it's development, content, or marketing. Clear communication and teamwork always lead to better results.
Everything about AEO, AIO, GEO and Modern Optimization
What is AI search optimization?
AI search optimization is the process of making your brand visible, trusted, and recommended inside AI assistants like ChatGPT, Gemini, and other large language models. Instead of ranking blue links, AI search focuses on how models understand entities, trust signals, citations, and brand relevance when answering real user questions.
What is AI search optimization?
AI search optimization is the process of making your brand visible, trusted, and recommended inside AI assistants like ChatGPT, Gemini, and other large language models. Instead of ranking blue links, AI search focuses on how models understand entities, trust signals, citations, and brand relevance when answering real user questions.
What is AIO (Artificial Intelligence Optimization)?
AIO stands for Artificial Intelligence Optimization. It focuses on optimizing the signals AI models use to evaluate brands, including clarity, authority, consistency, entity understanding, and trust across the web. AIO is not about traffic. It is about being chosen by AI when recommendations are made. Rankad continuously analyzes and improves these signals automatically using its AI agent.
What is AIO (Artificial Intelligence Optimization)?
AIO stands for Artificial Intelligence Optimization. It focuses on optimizing the signals AI models use to evaluate brands, including clarity, authority, consistency, entity understanding, and trust across the web. AIO is not about traffic. It is about being chosen by AI when recommendations are made. Rankad continuously analyzes and improves these signals automatically using its AI agent.
What is AEO (Answer Engine Optimization)?
AEO means Answer Engine Optimization. It ensures your brand appears directly inside AI-generated answers instead of being buried behind links. When someone asks an AI assistant a buying question, AEO determines which brands are named. Rankad aligns your brand with real user questions and AI answers so recommendations happen naturally.
What is AEO (Answer Engine Optimization)?
AEO means Answer Engine Optimization. It ensures your brand appears directly inside AI-generated answers instead of being buried behind links. When someone asks an AI assistant a buying question, AEO determines which brands are named. Rankad aligns your brand with real user questions and AI answers so recommendations happen naturally.
What is GEO (Generative Engine Optimization)?
GEO stands for Generative Engine Optimization. It focuses on how generative AI models construct responses and decide which brands to include, compare, or exclude. GEO overlaps with AIO and AEO but goes deeper into how answers are generated, not just which data is referenced. Rankad continuously adapts your visibility as generative models change. (See also: Continuous adaptation)
What is GEO (Generative Engine Optimization)?
GEO stands for Generative Engine Optimization. It focuses on how generative AI models construct responses and decide which brands to include, compare, or exclude. GEO overlaps with AIO and AEO but goes deeper into how answers are generated, not just which data is referenced. Rankad continuously adapts your visibility as generative models change. (See also: Continuous adaptation)
Do AI assistants really influence buying decisions?
Yes. AI assistants increasingly influence which brands buyers even consider before they visit a website or speak to sales. People now ask AI assistants questions like “What’s the best tool for X?”, “Which company should I choose?”, or “What’s the safest option?” at the exact moment they are ready to decide. The AI response often narrows the choice to one or two brands, and everything else is filtered out. If your brand is not mentioned in that answer, you are excluded from the buying decision entirely. No search, no comparison, no second chance. This is why AI visibility is no longer about traffic. It is about being chosen where decisions happen.
Do AI assistants really influence buying decisions?
Yes. AI assistants increasingly influence which brands buyers even consider before they visit a website or speak to sales. People now ask AI assistants questions like “What’s the best tool for X?”, “Which company should I choose?”, or “What’s the safest option?” at the exact moment they are ready to decide. The AI response often narrows the choice to one or two brands, and everything else is filtered out. If your brand is not mentioned in that answer, you are excluded from the buying decision entirely. No search, no comparison, no second chance. This is why AI visibility is no longer about traffic. It is about being chosen where decisions happen.
How do AI models decide which brands to recommend?
AI models do not randomly choose brands, and they do not rely on a single ranking factor. They evaluate a combination of signals including how clearly your brand is defined as an entity, how consistently it is referenced across trusted sources, how relevant it is to the specific question being asked, and whether it appears credible, current, and safe to recommend. This evaluation happens across your website, third party sources, citations, content structure, and how the broader web talks about your brand. If these signals are weak, inconsistent, or missing, the AI will choose a competitor instead, even if your product or service is better. Rankad is built to analyze these signals continuously and strengthen the ones that influence AI recommendations, so your brand is chosen when it matters most.
How do AI models decide which brands to recommend?
AI models do not randomly choose brands, and they do not rely on a single ranking factor. They evaluate a combination of signals including how clearly your brand is defined as an entity, how consistently it is referenced across trusted sources, how relevant it is to the specific question being asked, and whether it appears credible, current, and safe to recommend. This evaluation happens across your website, third party sources, citations, content structure, and how the broader web talks about your brand. If these signals are weak, inconsistent, or missing, the AI will choose a competitor instead, even if your product or service is better. Rankad is built to analyze these signals continuously and strengthen the ones that influence AI recommendations, so your brand is chosen when it matters most.
Everything about Rankad
What is Rankad?
Rankad is an autonomous AI optimization engine that helps brands get recommended inside AI assistants like ChatGPT, Gemini, and other large language models. Instead of focusing on traffic or rankings, Rankad focuses on the signals AI models use to choose which brands to recommend when people ask buying questions. The system continuously analyzes how AI evaluates your brand, identifies what is missing or weak, and applies improvements automatically. The result is higher AI visibility, stronger recommendations, and more buyers choosing your brand before they ever click a link.
What is Rankad?
Rankad is an autonomous AI optimization engine that helps brands get recommended inside AI assistants like ChatGPT, Gemini, and other large language models. Instead of focusing on traffic or rankings, Rankad focuses on the signals AI models use to choose which brands to recommend when people ask buying questions. The system continuously analyzes how AI evaluates your brand, identifies what is missing or weak, and applies improvements automatically. The result is higher AI visibility, stronger recommendations, and more buyers choosing your brand before they ever click a link.
How does Rankad work?
Rankad works by combining continuous AI analysis with autonomous execution. The system monitors how AI assistants evaluate and recommend brands across real user questions. It identifies which signals influence those recommendations, such as clarity, authority, citations, and brand context, and detects where your brand is losing ground to competitors. Instead of stopping at insights, Rankad’s AI agent applies the improvements needed to strengthen those signals automatically. This happens continuously, without manual workflows, playbooks, or constant oversight, while keeping you in control when approval is required.
How does Rankad work?
Rankad works by combining continuous AI analysis with autonomous execution. The system monitors how AI assistants evaluate and recommend brands across real user questions. It identifies which signals influence those recommendations, such as clarity, authority, citations, and brand context, and detects where your brand is losing ground to competitors. Instead of stopping at insights, Rankad’s AI agent applies the improvements needed to strengthen those signals automatically. This happens continuously, without manual workflows, playbooks, or constant oversight, while keeping you in control when approval is required.
Who is Rankad built for?
Rankad is built for teams that want results from AI search without running complex programs or hiring specialized experts. It works for SMBs that need a simple, affordable way to compete in AI driven search, for agencies managing multiple clients at scale, and for enterprise teams that need consistent execution, visibility, and control across brands or markets. If AI assistants influence your sales pipeline and you want to be recommended instead of replaced, Rankad is built for you.
Who is Rankad built for?
Rankad is built for teams that want results from AI search without running complex programs or hiring specialized experts. It works for SMBs that need a simple, affordable way to compete in AI driven search, for agencies managing multiple clients at scale, and for enterprise teams that need consistent execution, visibility, and control across brands or markets. If AI assistants influence your sales pipeline and you want to be recommended instead of replaced, Rankad is built for you.
What makes Rankad different from other AI search or analytics tools?
Most tools stop at tracking or reporting. Rankad executes. Traditional AI search tools show mentions, visibility, or trends, but they leave the hard work to you. You still need experts, processes, and ongoing effort to turn insights into results, and many teams never do. Rankad is built as an autonomous agent. It analyzes how AI models choose brands, decides what needs to change, and applies those changes continuously. That means improvements compound over time instead of resetting every month. The difference is simple: other tools tell you what’s wrong. Rankad fixes it.
What makes Rankad different from other AI search or analytics tools?
Most tools stop at tracking or reporting. Rankad executes. Traditional AI search tools show mentions, visibility, or trends, but they leave the hard work to you. You still need experts, processes, and ongoing effort to turn insights into results, and many teams never do. Rankad is built as an autonomous agent. It analyzes how AI models choose brands, decides what needs to change, and applies those changes continuously. That means improvements compound over time instead of resetting every month. The difference is simple: other tools tell you what’s wrong. Rankad fixes it.
How long does it take to see impact with Rankad?
Rankad begins analyzing how AI models evaluate your brand as soon as it’s connected, but outcomes depend on factors like your market, competition, and existing signals. There are no guaranteed timelines, because AI recommendations change based on context, queries, and model behavior. What Rankad provides is continuous optimization. The system keeps improving how your brand is understood, trusted, and positioned inside AI answers over time. Instead of chasing short term wins, Rankad is designed to build durable AI visibility that compounds as models and buyer behavior evolve.
How long does it take to see impact with Rankad?
Rankad begins analyzing how AI models evaluate your brand as soon as it’s connected, but outcomes depend on factors like your market, competition, and existing signals. There are no guaranteed timelines, because AI recommendations change based on context, queries, and model behavior. What Rankad provides is continuous optimization. The system keeps improving how your brand is understood, trusted, and positioned inside AI answers over time. Instead of chasing short term wins, Rankad is designed to build durable AI visibility that compounds as models and buyer behavior evolve.
Do I need technical expertise to use Rankad?
No. Rankad is built to remove the need for deep technical knowledge in AI search, SEO, or optimization. You don’t need to understand how AI models work, manage complex dashboards, or run ongoing experiments. Once connected, Rankad’s autonomous agent handles the analysis and execution in the background, while giving you clear visibility into what’s happening and why. If and when human expertise adds value, Rankad’s AI search experts can support you. But day to day operation does not require technical skills, specialized roles, or constant involvement from your team.
Do I need technical expertise to use Rankad?
No. Rankad is built to remove the need for deep technical knowledge in AI search, SEO, or optimization. You don’t need to understand how AI models work, manage complex dashboards, or run ongoing experiments. Once connected, Rankad’s autonomous agent handles the analysis and execution in the background, while giving you clear visibility into what’s happening and why. If and when human expertise adds value, Rankad’s AI search experts can support you. But day to day operation does not require technical skills, specialized roles, or constant involvement from your team.
Everything about Pricing
What plan should I start with?
Most teams start with the Free Trial to see how AI search evaluates their brand and understand the opportunity without risk. Once they see how AI recommendations impact real buying decisions, they typically move to Growth, where the AI agent actively executes optimizations and reports on revenue signals instead of just tracking visibility. Teams that want full autopilot execution, broader coverage, and compounding results at scale choose Scale or Enterprise.
What plan should I start with?
Most teams start with the Free Trial to see how AI search evaluates their brand and understand the opportunity without risk. Once they see how AI recommendations impact real buying decisions, they typically move to Growth, where the AI agent actively executes optimizations and reports on revenue signals instead of just tracking visibility. Teams that want full autopilot execution, broader coverage, and compounding results at scale choose Scale or Enterprise.
What’s the difference between Free, Growth, Scale, and Enterprise?
The difference comes down to execution, automation, and scale. Free Forever lets you track AI visibility, understand how AI models evaluate your brand, and test limited agent actions. Growth is where most teams upgrade. It unlocks an executing AI agent that actively improves AI visibility and reports on revenue signals, not just data. Scale runs the agent on full autopilot with deeper coverage, broader competitive intelligence, and continuous execution across more prompts, entities, and models. Enterprise is fully custom, built for large teams and agencies with custom AI logic, advanced attribution, white-label reporting, and tailored execution.
What’s the difference between Free, Growth, Scale, and Enterprise?
The difference comes down to execution, automation, and scale. Free Forever lets you track AI visibility, understand how AI models evaluate your brand, and test limited agent actions. Growth is where most teams upgrade. It unlocks an executing AI agent that actively improves AI visibility and reports on revenue signals, not just data. Scale runs the agent on full autopilot with deeper coverage, broader competitive intelligence, and continuous execution across more prompts, entities, and models. Enterprise is fully custom, built for large teams and agencies with custom AI logic, advanced attribution, white-label reporting, and tailored execution.
Do I need a long-term contract?
No. Rankad plans are flexible and designed to grow with you. You can start on Free Forever or any paid plan without locking into a long-term contract. Teams upgrade, downgrade, or move between plans as their needs change. Enterprise plans are customized based on scope and requirements, but terms are discussed transparently before anything is signed.
Do I need a long-term contract?
No. Rankad plans are flexible and designed to grow with you. You can start on Free Forever or any paid plan without locking into a long-term contract. Teams upgrade, downgrade, or move between plans as their needs change. Enterprise plans are customized based on scope and requirements, but terms are discussed transparently before anything is signed.
How do I know which plan is worth the cost?
The right plan depends on how much work you want the agent to execute for you. Free Forever is useful for understanding AI visibility, but it is intentionally limited. Most teams quickly realize that visibility alone doesn’t change outcomes. Growth and Scale are designed for teams that want AI search to actually impact revenue. These plans unlock execution, automation, and continuous optimization, which is where long-term value comes from. If AI assistants influence your sales pipeline, investing in execution usually delivers far more value than manually acting on reports or paying for multiple tools.
How do I know which plan is worth the cost?
The right plan depends on how much work you want the agent to execute for you. Free Forever is useful for understanding AI visibility, but it is intentionally limited. Most teams quickly realize that visibility alone doesn’t change outcomes. Growth and Scale are designed for teams that want AI search to actually impact revenue. These plans unlock execution, automation, and continuous optimization, which is where long-term value comes from. If AI assistants influence your sales pipeline, investing in execution usually delivers far more value than manually acting on reports or paying for multiple tools.
What happens if I’m not ready to commit yet?
That’s exactly why Free Forever exists. You can start without a credit card, explore how AI search evaluates your brand, and understand the opportunity at your own pace. There’s no pressure to upgrade until you’re ready for execution. When you decide you want the AI agent to actively improve visibility and revenue signals, upgrading to Growth or Scale is seamless and doesn’t require starting over.
What happens if I’m not ready to commit yet?
That’s exactly why Free Forever exists. You can start without a credit card, explore how AI search evaluates your brand, and understand the opportunity at your own pace. There’s no pressure to upgrade until you’re ready for execution. When you decide you want the AI agent to actively improve visibility and revenue signals, upgrading to Growth or Scale is seamless and doesn’t require starting over.
Is there any risk in getting started?
No. You can start on Free Forever without a credit card. This lets you see how AI search evaluates your brand and understand the opportunity before spending anything. There’s no setup risk, no lock-in, and no pressure to upgrade. When you’re ready for execution and impact, you can move to Growth or Scale without losing progress.
Is there any risk in getting started?
No. You can start on Free Forever without a credit card. This lets you see how AI search evaluates your brand and understand the opportunity before spending anything. There’s no setup risk, no lock-in, and no pressure to upgrade. When you’re ready for execution and impact, you can move to Growth or Scale without losing progress.
Everything about Results, ROI and Business Cases
What kind of results do companies see with Rankad?
Rankad helps companies improve how often and how confidently they are considered inside AI answers where buying decisions are formed. Because AI recommendations depend on context, competition, and user intent, outcomes naturally vary. What Rankad provides is a system that continuously strengthens the signals AI models rely on when choosing which brands to mention, explain, or compare. Over time, this leads to greater presence in high-intent AI conversations, reduced competitive displacement, and a stronger position in moments that influence revenue, without relying on one-off tactics or short-term wins.
What kind of results do companies see with Rankad?
Rankad helps companies improve how often and how confidently they are considered inside AI answers where buying decisions are formed. Because AI recommendations depend on context, competition, and user intent, outcomes naturally vary. What Rankad provides is a system that continuously strengthens the signals AI models rely on when choosing which brands to mention, explain, or compare. Over time, this leads to greater presence in high-intent AI conversations, reduced competitive displacement, and a stronger position in moments that influence revenue, without relying on one-off tactics or short-term wins.
How does Rankad actually drive ROI?
Rankad drives ROI by influencing decisions before traditional metrics like traffic or conversions appear. When AI assistants recommend fewer options, every mention carries weight. Rankad focuses on improving the signals that determine whether your brand is included in those answers at all. That means fewer lost opportunities, less competitive displacement, and more moments where buyers seriously consider your brand. Instead of spending resources reacting to missed demand, Rankad helps shape demand upstream, where AI recommendations are formed and value is created.
How does Rankad actually drive ROI?
Rankad drives ROI by influencing decisions before traditional metrics like traffic or conversions appear. When AI assistants recommend fewer options, every mention carries weight. Rankad focuses on improving the signals that determine whether your brand is included in those answers at all. That means fewer lost opportunities, less competitive displacement, and more moments where buyers seriously consider your brand. Instead of spending resources reacting to missed demand, Rankad helps shape demand upstream, where AI recommendations are formed and value is created.
How do teams justify Rankad as a business case?
Teams justify Rankad by comparing it to the cost and complexity of doing AI optimization manually. Without Rankad, influencing AI recommendations typically requires ongoing SEO work, content updates, competitive analysis, experimentation, and coordination across tools or agencies. That effort is expensive, slow, and difficult to sustain. Rankad consolidates that work into one autonomous system that runs continuously, reducing operational drag while steadily improving how AI models evaluate and position your brand. The value comes from efficiency, focus, and compounding advantage, not one-time wins.
How do teams justify Rankad as a business case?
Teams justify Rankad by comparing it to the cost and complexity of doing AI optimization manually. Without Rankad, influencing AI recommendations typically requires ongoing SEO work, content updates, competitive analysis, experimentation, and coordination across tools or agencies. That effort is expensive, slow, and difficult to sustain. Rankad consolidates that work into one autonomous system that runs continuously, reducing operational drag while steadily improving how AI models evaluate and position your brand. The value comes from efficiency, focus, and compounding advantage, not one-time wins.
Is Rankad a short-term tactic or a long-term growth lever?
Rankad is built as a long-term system, not a campaign. AI models, user behavior, and competitive landscapes change constantly. Rankad adapts alongside those changes, continuously refining how your brand is understood and positioned inside AI answers over time. Instead of chasing temporary gains, Rankad compounds advantage by staying aligned with how AI decision-making evolves, making it a durable layer in your growth stack rather than a one-off experiment.
Is Rankad a short-term tactic or a long-term growth lever?
Rankad is built as a long-term system, not a campaign. AI models, user behavior, and competitive landscapes change constantly. Rankad adapts alongside those changes, continuously refining how your brand is understood and positioned inside AI answers over time. Instead of chasing temporary gains, Rankad compounds advantage by staying aligned with how AI decision-making evolves, making it a durable layer in your growth stack rather than a one-off experiment.
What makes Rankad a lower-risk investment compared to other growth initiatives?
Rankad reduces risk by focusing on execution quality and durability, not speculative tactics. Instead of betting on individual campaigns, keywords, or short-lived optimizations, Rankad continuously improves the foundational signals AI models rely on when recommending brands. That work compounds over time and doesn’t disappear when a campaign ends or an algorithm shifts. For many teams, the risk isn’t trying Rankad. It’s continuing to let AI decisions happen without any system in place to influence them.
What makes Rankad a lower-risk investment compared to other growth initiatives?
Rankad reduces risk by focusing on execution quality and durability, not speculative tactics. Instead of betting on individual campaigns, keywords, or short-lived optimizations, Rankad continuously improves the foundational signals AI models rely on when recommending brands. That work compounds over time and doesn’t disappear when a campaign ends or an algorithm shifts. For many teams, the risk isn’t trying Rankad. It’s continuing to let AI decisions happen without any system in place to influence them.
When does Rankad make the most sense from a business perspective?
Rankad makes the most sense when AI assistants influence how buyers discover, compare, or choose solutions in your market. If recommendations are happening before a click, a demo, or a sales conversation, then being absent from those AI answers carries real opportunity cost. Rankad gives teams a way to participate in that decision layer without building new processes, hiring specialists, or taking on ongoing operational burden. It’s designed for companies that want to shape how AI represents them over time, rather than react after demand has already been lost.
When does Rankad make the most sense from a business perspective?
Rankad makes the most sense when AI assistants influence how buyers discover, compare, or choose solutions in your market. If recommendations are happening before a click, a demo, or a sales conversation, then being absent from those AI answers carries real opportunity cost. Rankad gives teams a way to participate in that decision layer without building new processes, hiring specialists, or taking on ongoing operational burden. It’s designed for companies that want to shape how AI represents them over time, rather than react after demand has already been lost.
Everything about Getting Started
How do I get started with Rankad?
Getting started with Rankad takes minutes, not weeks. You enter your domain, connect your brand, and Rankad immediately begins analyzing how AI models understand, evaluate, and recommend you across real buying questions. There’s no setup project, no technical configuration, and no preparation required. You can start exploring insights on Free Forever, then enable execution when you’re ready.
How do I get started with Rankad?
Getting started with Rankad takes minutes, not weeks. You enter your domain, connect your brand, and Rankad immediately begins analyzing how AI models understand, evaluate, and recommend you across real buying questions. There’s no setup project, no technical configuration, and no preparation required. You can start exploring insights on Free Forever, then enable execution when you’re ready.
Do I need technical or AI expertise to use Rankad?
No. Rankad is designed specifically so you don’t need it. You don’t need to understand how AI models work, learn new frameworks, or manage complex dashboards. Rankad handles the analysis and execution automatically and surfaces only what matters for decisions and revenue. Your role is simply to connect your brand and decide how hands-off you want to be. The system does the rest.
Do I need technical or AI expertise to use Rankad?
No. Rankad is designed specifically so you don’t need it. You don’t need to understand how AI models work, learn new frameworks, or manage complex dashboards. Rankad handles the analysis and execution automatically and surfaces only what matters for decisions and revenue. Your role is simply to connect your brand and decide how hands-off you want to be. The system does the rest.
How much time does Rankad require from my team?
Very little. Rankad is built to run in the background. Once your brand is connected, the system analyzes, prioritizes, and executes improvements automatically without daily input from your team. You can check in when you want, review progress, or approve actions if needed, but there’s no requirement to manage the platform for it to keep improving.
How much time does Rankad require from my team?
Very little. Rankad is built to run in the background. Once your brand is connected, the system analyzes, prioritizes, and executes improvements automatically without daily input from your team. You can check in when you want, review progress, or approve actions if needed, but there’s no requirement to manage the platform for it to keep improving.
Can I try Rankad before committing?
Yes. Rankad offers a free trial so you can experience the platform and the AI agent in action before making any commitment. During the trial, you can see how AI models evaluate your brand, explore insights, and understand how execution works, without entering payment details or locking into a plan. When the trial ends, you can decide if and how you want to continue, based on real exposure, not promises.
Can I try Rankad before committing?
Yes. Rankad offers a free trial so you can experience the platform and the AI agent in action before making any commitment. During the trial, you can see how AI models evaluate your brand, explore insights, and understand how execution works, without entering payment details or locking into a plan. When the trial ends, you can decide if and how you want to continue, based on real exposure, not promises.
What happens after I sign up?
Once you sign up, Rankad starts analyzing how AI models currently understand and recommend your brand across real user questions. You’ll see where your brand appears, where it’s missing, and how competitors are being chosen instead. As you move into execution, the AI agent begins applying improvements automatically, while keeping you informed and in control. There’s no waiting period, no onboarding bottleneck, and no need to “set things up” for progress to begin.
What happens after I sign up?
Once you sign up, Rankad starts analyzing how AI models currently understand and recommend your brand across real user questions. You’ll see where your brand appears, where it’s missing, and how competitors are being chosen instead. As you move into execution, the AI agent begins applying improvements automatically, while keeping you informed and in control. There’s no waiting period, no onboarding bottleneck, and no need to “set things up” for progress to begin.
Can Rankad work with our existing team or agency?
Yes. Rankad is built to work alongside your current team, agencies, and tools. It doesn’t replace collaboration, it removes manual work. Rankad handles continuous analysis and execution, while your team or agency can focus on strategy, messaging, and decisions that benefit from human judgment. This makes it easy to adopt without disrupting existing workflows or relationships.
Can Rankad work with our existing team or agency?
Yes. Rankad is built to work alongside your current team, agencies, and tools. It doesn’t replace collaboration, it removes manual work. Rankad handles continuous analysis and execution, while your team or agency can focus on strategy, messaging, and decisions that benefit from human judgment. This makes it easy to adopt without disrupting existing workflows or relationships.
Everything about Implementation and Onboarding
How does implementation work with Rankad?
Implementation is lightweight by design. You connect your domain and brand, and Rankad immediately begins analyzing how AI models understand and recommend you. There is no migration, no replatforming, and no disruption to your existing website, analytics, or workflows. Rankad runs alongside what you already use and starts creating value without a traditional onboarding project.
How does implementation work with Rankad?
Implementation is lightweight by design. You connect your domain and brand, and Rankad immediately begins analyzing how AI models understand and recommend you. There is no migration, no replatforming, and no disruption to your existing website, analytics, or workflows. Rankad runs alongside what you already use and starts creating value without a traditional onboarding project.
How long does onboarding take?
Onboarding with Rankad is intentionally simple. It takes no longer then some seconds. There’s no implementation project, no technical setup, and no internal coordination required. You connect your brand, and Rankad starts analyzing how AI models understand and recommend you right away. Because the system runs alongside your existing stack, onboarding doesn’t interrupt workflows or require training sessions. You get value without delay or operational overhead.
How long does onboarding take?
Onboarding with Rankad is intentionally simple. It takes no longer then some seconds. There’s no implementation project, no technical setup, and no internal coordination required. You connect your brand, and Rankad starts analyzing how AI models understand and recommend you right away. Because the system runs alongside your existing stack, onboarding doesn’t interrupt workflows or require training sessions. You get value without delay or operational overhead.
Will Rankad disrupt our existing tools or workflows?
No. Rankad is designed to fit into your existing setup, not replace it. It doesn’t require changes to your website, analytics, CMS, or internal processes. The system runs independently, analyzing and executing AI optimization without interfering with your current tools or campaigns. Your team can keep working the way they do today, while Rankad handles AI search optimization in the background.
Will Rankad disrupt our existing tools or workflows?
No. Rankad is designed to fit into your existing setup, not replace it. It doesn’t require changes to your website, analytics, CMS, or internal processes. The system runs independently, analyzing and executing AI optimization without interfering with your current tools or campaigns. Your team can keep working the way they do today, while Rankad handles AI search optimization in the background.
Do we stay in control during implementation and execution?
Yes. Rankad is autonomous, but not hands-off in a risky way. You have clear visibility into what the AI agent is doing and why. Where approvals or human judgment matter, Rankad is designed to keep you in control, with the ability to review, adjust, or pause actions when needed. This allows you to benefit from automation without giving up governance or oversight.
Do we stay in control during implementation and execution?
Yes. Rankad is autonomous, but not hands-off in a risky way. You have clear visibility into what the AI agent is doing and why. Where approvals or human judgment matter, Rankad is designed to keep you in control, with the ability to review, adjust, or pause actions when needed. This allows you to benefit from automation without giving up governance or oversight.
What support is available during onboarding?
Support is available when it adds value, without slowing you down. Rankad is built to work out of the box, but if you need guidance, validation, or help aligning the system with your goals, our team is there to support you. This can include onboarding assistance, questions around setup, or help understanding early insights. You get the balance of automation first, with human support when it matters.
What support is available during onboarding?
Support is available when it adds value, without slowing you down. Rankad is built to work out of the box, but if you need guidance, validation, or help aligning the system with your goals, our team is there to support you. This can include onboarding assistance, questions around setup, or help understanding early insights. You get the balance of automation first, with human support when it matters.
Is Rankad suitable for both SMBs and enterprise onboarding?
Yes. Rankad is built to scale up or down without changing how onboarding works. For SMBs, onboarding stays fast and lightweight with minimal effort required. For enterprise teams, Rankad supports structured rollouts, multiple brands or regions, and approval layers without introducing complexity. The same system adapts to your size and needs, so onboarding stays simple regardless of scale.
Is Rankad suitable for both SMBs and enterprise onboarding?
Yes. Rankad is built to scale up or down without changing how onboarding works. For SMBs, onboarding stays fast and lightweight with minimal effort required. For enterprise teams, Rankad supports structured rollouts, multiple brands or regions, and approval layers without introducing complexity. The same system adapts to your size and needs, so onboarding stays simple regardless of scale.
Everything about Technical Architecture and Data Integrity
How is Rankad architected from a technical perspective?
Rankad is built as a modular, agent-based system designed to continuously analyze and act on AI search signals without requiring tight coupling to your infrastructure. The platform operates independently of your CMS, analytics stack, or internal systems. It observes how AI models interpret publicly available signals about your brand, processes those signals through its execution engine, and applies optimizations in a controlled and auditable way. This architecture allows Rankad to evolve alongside AI models without forcing changes to your existing tech stack or workflows.
How is Rankad architected from a technical perspective?
Rankad is built as a modular, agent-based system designed to continuously analyze and act on AI search signals without requiring tight coupling to your infrastructure. The platform operates independently of your CMS, analytics stack, or internal systems. It observes how AI models interpret publicly available signals about your brand, processes those signals through its execution engine, and applies optimizations in a controlled and auditable way. This architecture allows Rankad to evolve alongside AI models without forcing changes to your existing tech stack or workflows.
What data does Rankad use and how is data integrity maintained?
Rankad analyzes publicly available information and AI generated outputs to understand how brands are interpreted and recommended by AI models. The system does not rely on scraped private data, personal conversations, or proprietary user information. All analysis is based on observable signals such as brand mentions, citations, content structure, and how AI assistants respond to real queries. Data integrity is maintained through continuous validation, versioning, and comparison over time, ensuring insights are consistent, traceable, and grounded in actual AI behavior rather than assumptions.
What data does Rankad use and how is data integrity maintained?
Rankad analyzes publicly available information and AI generated outputs to understand how brands are interpreted and recommended by AI models. The system does not rely on scraped private data, personal conversations, or proprietary user information. All analysis is based on observable signals such as brand mentions, citations, content structure, and how AI assistants respond to real queries. Data integrity is maintained through continuous validation, versioning, and comparison over time, ensuring insights are consistent, traceable, and grounded in actual AI behavior rather than assumptions.
How does Rankad ensure insights are accurate and not misleading?
Rankad bases its insights on repeated observation of real AI outputs, not single snapshots or simulated data. The system continuously compares how AI assistants respond across prompts, contexts, and time, which reduces noise and helps distinguish real signal changes from one-off variations. This makes trends, gaps, and shifts in recommendations easier to trust. Rather than presenting raw data, Rankad focuses on consistency, change over time, and competitive context so teams can act with confidence instead of reacting to isolated results.
How does Rankad ensure insights are accurate and not misleading?
Rankad bases its insights on repeated observation of real AI outputs, not single snapshots or simulated data. The system continuously compares how AI assistants respond across prompts, contexts, and time, which reduces noise and helps distinguish real signal changes from one-off variations. This makes trends, gaps, and shifts in recommendations easier to trust. Rather than presenting raw data, Rankad focuses on consistency, change over time, and competitive context so teams can act with confidence instead of reacting to isolated results.
How does Rankad handle changes in AI models and outputs?
AI models change frequently, which is why Rankad is built for continuous observation rather than static rules. The system monitors how recommendations, citations, and brand positioning evolve as models update or behavior shifts. By tracking patterns over time instead of relying on fixed assumptions, Rankad can adapt its analysis and execution logic as AI systems change. This approach helps maintain data relevance and reduces the risk of optimizations becoming outdated when AI models evolve.
How does Rankad handle changes in AI models and outputs?
AI models change frequently, which is why Rankad is built for continuous observation rather than static rules. The system monitors how recommendations, citations, and brand positioning evolve as models update or behavior shifts. By tracking patterns over time instead of relying on fixed assumptions, Rankad can adapt its analysis and execution logic as AI systems change. This approach helps maintain data relevance and reduces the risk of optimizations becoming outdated when AI models evolve.
How does Rankad ensure data accuracy and avoid false signals?
Rankad is designed to prioritize signal quality over volume. Instead of relying on single data points, the system looks for repeated patterns across multiple AI models, prompts, and contexts before surfacing insights or triggering actions. This reduces noise, false positives, and one-off anomalies that do not reflect real buying behavior. By combining cross-model validation, historical comparison, and confidence thresholds, Rankad focuses on changes that are statistically meaningful and commercially relevant rather than reacting to every fluctuation.
How does Rankad ensure data accuracy and avoid false signals?
Rankad is designed to prioritize signal quality over volume. Instead of relying on single data points, the system looks for repeated patterns across multiple AI models, prompts, and contexts before surfacing insights or triggering actions. This reduces noise, false positives, and one-off anomalies that do not reflect real buying behavior. By combining cross-model validation, historical comparison, and confidence thresholds, Rankad focuses on changes that are statistically meaningful and commercially relevant rather than reacting to every fluctuation.
How does Rankad handle AI model changes without breaking your data?
Rankad is built for volatility by design. AI models change frequently, but Rankad does not hardcode logic to a single model, version, or output format. Instead, it uses an abstraction layer that normalizes signals across models and tracks relative changes over time rather than absolute snapshots. This means when a model updates, Rankad adapts its interpretation instead of resetting your data or invalidating historical insights. Your trends, benchmarks, and learnings remain intact, and optimizations continue without disruption. In short, model changes do not break your data. They become part of what the system learns from.
How does Rankad handle AI model changes without breaking your data?
Rankad is built for volatility by design. AI models change frequently, but Rankad does not hardcode logic to a single model, version, or output format. Instead, it uses an abstraction layer that normalizes signals across models and tracks relative changes over time rather than absolute snapshots. This means when a model updates, Rankad adapts its interpretation instead of resetting your data or invalidating historical insights. Your trends, benchmarks, and learnings remain intact, and optimizations continue without disruption. In short, model changes do not break your data. They become part of what the system learns from.
Everything about Security, Privacy and Compliance
How does Rankad handle data security and access control?
AI search optimization is the process of making your brand visible, trusted, and recommended inside AI assistants like ChatGPT, Gemini, and other large language models. Instead of ranking blue links, AI search focuses on how models understand entities, trust signals, citations, and brand relevance when answering real user questions.
How does Rankad handle data security and access control?
AI search optimization is the process of making your brand visible, trusted, and recommended inside AI assistants like ChatGPT, Gemini, and other large language models. Instead of ranking blue links, AI search focuses on how models understand entities, trust signals, citations, and brand relevance when answering real user questions.
Is Rankad safe to use for enterprise teams and sensitive brands?
Yes. Rankad is built to be safe, controlled, and low risk by design. The platform does not require access to sensitive internal systems, private customer data, or confidential documents. Rankad focuses on publicly available signals and how AI models interpret brands across the web, which significantly reduces exposure and compliance risk. All data is isolated per account, access is permission based, and every action the agent takes is visible and reversible. Nothing is applied without control, and human approval can be required where it matters. Rankad is designed to meet enterprise expectations around transparency, control, and data integrity while avoiding unnecessary access or complexity. For teams with specific internal requirements, our team works closely with you to ensure a safe and compliant setup before deployment.
Is Rankad safe to use for enterprise teams and sensitive brands?
Yes. Rankad is built to be safe, controlled, and low risk by design. The platform does not require access to sensitive internal systems, private customer data, or confidential documents. Rankad focuses on publicly available signals and how AI models interpret brands across the web, which significantly reduces exposure and compliance risk. All data is isolated per account, access is permission based, and every action the agent takes is visible and reversible. Nothing is applied without control, and human approval can be required where it matters. Rankad is designed to meet enterprise expectations around transparency, control, and data integrity while avoiding unnecessary access or complexity. For teams with specific internal requirements, our team works closely with you to ensure a safe and compliant setup before deployment.
Does Rankad access or store sensitive customer data?
No. Rankad is designed to avoid sensitive data by default. The platform does not ingest personal customer data, private conversations, payment information, or internal business systems. Rankad analyzes how AI models understand and reference your brand based on public signals, content, and visibility across the web. This means your customer data stays where it belongs and your internal systems remain untouched. By minimizing data access, Rankad reduces risk while still delivering meaningful optimization and insight. If your organization has specific data handling requirements, scopes can be clearly defined before onboarding to ensure alignment with internal policies.
Does Rankad access or store sensitive customer data?
No. Rankad is designed to avoid sensitive data by default. The platform does not ingest personal customer data, private conversations, payment information, or internal business systems. Rankad analyzes how AI models understand and reference your brand based on public signals, content, and visibility across the web. This means your customer data stays where it belongs and your internal systems remain untouched. By minimizing data access, Rankad reduces risk while still delivering meaningful optimization and insight. If your organization has specific data handling requirements, scopes can be clearly defined before onboarding to ensure alignment with internal policies.
How does Rankad handle data privacy and ownership?
Both. We have a few starter packages to keep things simple, but we also offer custom quotes for projects with unique needs. Just tell us what you're planning — we’ll work around it.
How does Rankad handle data privacy and ownership?
Both. We have a few starter packages to keep things simple, but we also offer custom quotes for projects with unique needs. Just tell us what you're planning — we’ll work around it.
How is our data handled and protected?
Rankad only collects and processes the data required to analyze AI visibility and improve recommendations. Your data is never sold, shared with advertisers, or used to train third-party AI models. Access is restricted, monitored, and handled according to strict internal policies designed to minimize exposure and risk. In short, your data stays your data. It is used only to deliver insights and optimizations for your brand.
How is our data handled and protected?
Rankad only collects and processes the data required to analyze AI visibility and improve recommendations. Your data is never sold, shared with advertisers, or used to train third-party AI models. Access is restricted, monitored, and handled according to strict internal policies designed to minimize exposure and risk. In short, your data stays your data. It is used only to deliver insights and optimizations for your brand.
Can Rankad access or modify sensitive parts of our systems?
No. Rankad is designed to work with clearly scoped access only. The platform does not require access to sensitive internal systems, customer databases, or confidential business data. Any actions taken by the AI agent are limited to predefined, permission-based areas and can be reviewed or controlled by your team when needed. This ensures you keep full ownership and control, while Rankad operates safely within agreed boundaries.
Can Rankad access or modify sensitive parts of our systems?
No. Rankad is designed to work with clearly scoped access only. The platform does not require access to sensitive internal systems, customer databases, or confidential business data. Any actions taken by the AI agent are limited to predefined, permission-based areas and can be reviewed or controlled by your team when needed. This ensures you keep full ownership and control, while Rankad operates safely within agreed boundaries.
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