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Best AI Search Engines To Try Right Now



Best AI Search Engines To Try Right Now

AI-powered search engines are a new breed redefining the search experience as we know it.

And when we talk about AI-powered search engines, Bing and Google SGE (Search Generative Experience) are currently the two that rise to the top.

For some time, they have been the most popular and widely recognizable names in AI search engines – and, as such, the ones that get the most attention.

But as with most things, the landscape is far from stagnant. Today, there are many other AI search engines out there that are just as useful as Bing and Google – and, in some ways, even better.

From privacy-focused search engines to those that prioritize publisher sourcing, we have curated a list of the six best AI search engines that exist right now and what you need to know about them.


Notably, at least one of them boasts a paid version with such a generous number of queries per day that some argue it surpasses the offerings of OpenAI’s ChatGPT Plus.

Let’s dive in.

1. Andi Search

Andi Search is a startup AI search engine that offers an interpretation of a better way to explore the Internet and obtain knowledge.

After a while of using Andi, one gets a sense that there really is a better way to present information.

It also becomes apparent that Bing and Google SGE haven’t strayed far from the old 10 blue links paradigm.

There are three things that make Andi stand out:

  • The interface uses AI throughout the entire search results, not just at the top of the page the way Bing and Google SGE do.
  • Images, summaries, and options are offered in a way that makes sense contextually.
  • All on-page elements work together to communicate the information users are seeking.

Andi Is More Than A Text-Based Search Engine

Humans are highly visual, and Andi does a good job of presenting information not just with text but with images, too.

Using Andi, it becomes apparent that both Bing and Google SGE are traditional search engines with an AI chatbox at the top of the page.

What Is Andi AI Search?

Andi is a factually grounded AI search engine that was purposely created to offer trustworthy answers while avoiding hallucinations that are common to GPT-based apps.

It offers keyword search results, answers complex multi-part questions, and fully understands natural language input.

Technology Used By Andi

Andi Search uses a mix of technologies.

In a 2022 Q&A, Andi Search engineers said they use several commercial and open-source Large Language Models (LLMs), knowledge graphs, and Google, Bing, and other search engines (50% of the time in 2022).

Andi AI Search Results

I asked Andi a complex question:

"Please tell me about the fictional star wars character Ahsoka and also explain if she is one of the most skilled Jedi of all time."

The answer was in the form of a short summary and a link to the source of the information, with an option to show the full search results or to summarize an answer to the question.

The summary provided correctly answered my complex question, even the part about whether the fictional character Ahsoka Tano is the most skilled Jedi of all time.

Video Of Search Results From Websites

On a desktop, the right-hand side contains a panel with the search results.

The results are not in the form of a standard 10 blue links, but rather, they consist of the featured image with text from the webpage.

Andi is currently in a Beta testing stage, but it is freely available to use – no need to sign up or have an account.

Andi Search And Privacy

Andi is a privacy-first AI company. It doesn’t store cookies, doesn’t share data, and no information is available to any employee of the company.


It even blocks Google’s FLoC tracking technology so that Google can’t follow you onto Andi.

Controversial Feature

Andi is a fine search engine in many ways, but there is one feature called Reader that publishers may not appreciate.

Screenshot Of Andi Reader Button

Screenshot from Andi Reader, September 2023Andi Reader button

Clicking on the Read button reveals the entire webpage for users to read without visiting the website.

Below is a screenshot that shows how Andi publishes a snapshot of the webpage (content blurred by me):

Screenshot Of Andi Search Reader

Andi Search ReaderScreenshot from Andi Reader, September 2023Andi Search Reader

Summary Of Andi Search

Andi is truly a rethink of how the search engines of today should function. It encourages users to rediscover the best that the web has to offer.

On the other hand, the engineers behind Andi may want to consider that publishers and search engines are an ecosystem that are dependent on each other.

2. Metaphor AI Search

There are many AI startups that are visualizing different ways to surface internet data that leverage the power of AI. That approach does away with traditional crawlers and indexers.

Metaphor is an example of the out-of-the-box use of large language models.


A Q&A on Y Combinator/Hacker News reveals that the engineer behind Metaphor uses what he calls next link prediction.

The intuition underlying the approach is that training LLMs and indexing websites are somewhat similar.

What they did was create a model architecture that had the concept of links baked in.

An interesting feature of Metaphor is that growing the index of sites doesn’t require retraining the entire language model. It’s simply a matter of adding the additional data.

How Metaphor AI Search Works

Approaching Metaphor, it’s important to keep in mind that this isn’t a traditional style search engine.

It’s surfacing links.


Furthermore, users can select what kinds of links to show.

The user-selectable categories are:

  • Tweets.
  • Wiki.
  • News.
  • Research Papers.
  • Podcasts.
  • Events.
  • Blogs.
  • GitHub.
  • Companies.
  • Recipes.
  • All of the Above.

Metaphor Search Results

Searching for recipes shows results that are different from Google and Bing, in a good way.

A search for authentic Spanish rice recipes as well as authentic mujadara recipes. Metaphor surfaced links to websites with authentic recipes.

The quality of the sites was different from the dumbed-down and inauthentic recipes sometimes shown on Google.

Searches on Metaphor sometimes don’t generate what you’re looking for. For example, searching for SEO in the News category yielded irrelevant results.

Summary Of Metaphor

Metaphor is worth giving a try because it may be useful for certain kinds of searches.


It’s not a general search engine, and it doesn’t claim to be. It’s something different, and that can be refreshing sometimes.

Nevertheless, Metaphor is still in the early stages of development, and it shows in some searches.

3. Brave AI Search Summarizer

Brave searchScreenshot from Brave, September 2023Brave search

Brave Search is a privacy-first search engine.

AI is deployed in a way that complements search and does not attempt to be a chatbot – it simply serves the goal of offering information.

Brave uses its own LLMs to assess the ranked webpages and offer a summarization. This function is called the Summarizer, which users can opt out of if they wish.

The Summarizer isn’t invoked for every search, only about 17% of searches will spawn the feature.

What’s great about the Summarizer is that it links to sources.


The screenshot below has the links circled in red.

Screenshot Of Brave Summarizer

Screenshot Of Brave SummarizerScreenshot from Brave Summarizer, September 2023Screenshot Of Brave Summarizer

Another use of AI is to generate webpage descriptions so that users can read a brief of what’s contained on the webpage.

The technology powering Brave consists of three LLMs trained for:

  • Question answering and improving search results.
  • Classification to weed out undesirable search results.
  • Summarizer and paraphrasing model add the final touches.

Brave Search Language Models

Brave Search uses two open-source language models that are available at Hugging Face.

The first language model is called BART (not to be confused with BERT, which is something different).

The second language model used by Brave is DeBERTa, which is a hybrid model based on Google’s BERT and Meta’s RoBERTa. DeBERTa is said to be an improvement over BERT and ROBERTa.

Brave Search does not use Bing or Google search, it has its own webpage index.

Brave Search Summary

Brave Search is perfect for users who want a search engine that respects privacy, is easy to use, and is useful.


4. YOU AI Search Engine

YOU is an AI search engine that combines a large language model with up-to-date citations to websites, which makes it more than just a search engine. calls itself YouChat, a search assistant that’s in the search engine.

Notable about YouChat is that, while it’s a privacy-first search assistant, it claims that it also gets better the more you use it.

Another outstanding feature is that YouChat can respond to the latest news and recent events.

YouChat can write code, summarize complex topics, generate images, write code, and create content (in any language). features YouAgent, an AI agent that writes code and can run it in its own environment, then take further action based on the output.


It’s available at and available as an app for Android and iPhone and as a Chrome extension.

All versions of respect privacy and do not sell user data to advertisers.

The web version of answers questions with answers summarized from websites that are linked to from the answer. SERPs With Links To Websites

The 6 Best AI Search Engines To Try Right NowThe 6 Best AI Search Engines To Try Right Now

There are traditional search results in a right-hand panel, which consists of links to videos and websites.

Links To Webpages & Videos On Side Panel

The 6 Best AI Search Engines To Try Right NowThe 6 Best AI Search Engines To Try Right Now

YOU is available in a free and paid version.

The free version of You offers unlimited chat-based searches. It also provides a limited amount of AI image and writing generations (ten each).


The paid versions, You Pro for $9.99/month and YouPro for Educational for $6.99/month, offer unlimited AI image and writing generations, personalized machine learning, and priority access.

Subscriptions are available at a lower price when paid on a yearly basis. Summary is a unique personalized search destination tuned to help users not just research topics but get things done.

The AI search engine answers questions in natural language while also citing links to websites and videos that offer comprehensive coverage of the topic. also provides chat-based AI tools that are capable of taking that research and creating something new with it.


Phind calls itself a generative AI search engine for developers.


On August 28, 2023, it announced a new LLM called Phind-CodeLlama-34B-v2 that outperforms GPT-4 on a benchmark called HumanEval.

The technology underpinning Phind is a serious contender.

While it self-describes as AI search for developers, it does a great job of surfacing answers from trustworthy websites.

A drop down menu next to the search box allows users to choose from GPT-3.5 Turbo or the Phind Model (unlimited uses) and limited use of GPT-4.

Phind can answer complex questions such as, “How did Facebook become so popular?” or “What marketing lessons can be learned from how Shein promotes itself?” It can also respond to follow-up questions.

But the search results aren’t always perfect.


A query for “What is a Google-friendly way to build links to a website?” resulted in several valid suggestions but also the recommendation of guest posting for links.

A follow-up question resulted in a response that backtracked on the guest posting suggestion.

Summary Of Phind

Phind is a fine way to interact with a GPT-3.5-based search engine that can also output essays and solve other problems.

Users can sign in to save their chats.

6. is a self-described answer engine.

It offers natural language answers to questions that are up to date, including being able to answer questions about the weather.


Perplexity is powered by LLMs, Internet data, and its updated version of Google’s PageRank, which creates a link graph of trustworthy websites. is a serious contender in AI Search.

It was founded by people with links to DeepMind and OpenAI and is funded by leading Silicon Valley investors.

The search engine itself offers in-depth answers and suggests follow-up questions to dig even deeper.

Perplexity is even able to mix different kinds of information and come up with perfect answers.

For example, I asked it to write an article about SEO that corresponds to Ernest Hemingway’s writing style.

"Please create an informational article about search engine optimization, that is done in the style of Ernest Hemingway"

It offered suggestions like:

“Keep it simple: Hemingway’s writing style is known for its simplicity and clarity.

Similarly, when it comes to SEO, it’s important to keep your content simple and easy to understand.

Avoid using overly technical jargon or complex sentence structures that might confuse your readers.

…Hemingway’s writing style can be a useful guide for creating SEO-friendly content. By focusing on simplicity, readability, and clarity, you can create content that is both engaging and optimized for search engines.”

It’s not perfect, though.

I asked it about former Googler Matt Cutts, and it provided a comprehensive answer that also cited Matt as the founder of an SEO consultancy.


The wrong answer came from a LinkedIn page where the name of the consultancy was found in a sidebar containing people who are connected to him on LinkedIn.

What I think may have happened is that the crawler may not yet be able to separate the main content of a webpage from the rest of the content.

I asked it the link building question, “What is a Google-friendly way to build links to a website?” and it gave a reasonable answer.

A useful feature, as mentioned earlier, is the suggested follow-up topics. Perplexity labels them as “Related.”

The related topics offered for the link building question were:

  • “What are some effective link building strategies for SEO.”
  • How to find high-quality websites to link to your site.
  • What are some common mistakes to avoid when building links for SEO.”

Screenshot Of Related Topics Suggestions Related questionsScreenshot from, September Related questions Is Publisher-Friendly

Something that should be mentioned is that is publisher-friendly.

It does a great job of linking to the websites from which the answers were sourced.

Advertisement answers to Screenshot from, September answers to Summary

Perplexity is much more than a search engine, it’s a true answer engine.

It reimagines what question answering can be and does a great job of providing answers and also encouraging exploration with suggestions for related topics.

AI Search Engine Future Is Now

It’s been decades since users had such a vast choice in search engines.

There have never been so many viable alternatives to Google as there are today.

Generative AI is creating new ways to discover accurate and up-to-date information.

The “organic” 10 blue links are increasingly becoming a thing of the past.

Give some of these free AI search engines a try, because many are every bit as good as the top two.


More resources:

Featured image by Shutterstock/SvetaZi

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Measuring Content Impact Across The Customer Journey




Measuring Content Impact Across The Customer Journey

Understanding the impact of your content at every touchpoint of the customer journey is essential – but that’s easier said than done. From attracting potential leads to nurturing them into loyal customers, there are many touchpoints to look into.

So how do you identify and take advantage of these opportunities for growth?

Watch this on-demand webinar and learn a comprehensive approach for measuring the value of your content initiatives, so you can optimize resource allocation for maximum impact.

You’ll learn:

  • Fresh methods for measuring your content’s impact.
  • Fascinating insights using first-touch attribution, and how it differs from the usual last-touch perspective.
  • Ways to persuade decision-makers to invest in more content by showcasing its value convincingly.

With Bill Franklin and Oliver Tani of DAC Group, we unravel the nuances of attribution modeling, emphasizing the significance of layering first-touch and last-touch attribution within your measurement strategy. 

Check out these insights to help you craft compelling content tailored to each stage, using an approach rooted in first-hand experience to ensure your content resonates.


Whether you’re a seasoned marketer or new to content measurement, this webinar promises valuable insights and actionable tactics to elevate your SEO game and optimize your content initiatives for success. 

View the slides below or check out the full webinar for all the details.

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How to Find and Use Competitor Keywords



How to Find and Use Competitor Keywords

Competitor keywords are the keywords your rivals rank for in Google’s search results. They may rank organically or pay for Google Ads to rank in the paid results.

Knowing your competitors’ keywords is the easiest form of keyword research. If your competitors rank for or target particular keywords, it might be worth it for you to target them, too.

There is no way to see your competitors’ keywords without a tool like Ahrefs, which has a database of keywords and the sites that rank for them. As far as we know, Ahrefs has the biggest database of these keywords.

How to find all the keywords your competitor ranks for

  1. Go to Ahrefs’ Site Explorer
  2. Enter your competitor’s domain
  3. Go to the Organic keywords report

The report is sorted by traffic to show you the keywords sending your competitor the most visits. For example, Mailchimp gets most of its organic traffic from the keyword “mailchimp.”

Mailchimp gets most of its organic traffic from the keyword, “mailchimp”.Mailchimp gets most of its organic traffic from the keyword, “mailchimp”.

Since you’re unlikely to rank for your competitor’s brand, you might want to exclude branded keywords from the report. You can do this by adding a Keyword > Doesn’t contain filter. In this example, we’ll filter out keywords containing “mailchimp” or any potential misspellings:

Filtering out branded keywords in Organic keywords reportFiltering out branded keywords in Organic keywords report

If you’re a new brand competing with one that’s established, you might also want to look for popular low-difficulty keywords. You can do this by setting the Volume filter to a minimum of 500 and the KD filter to a maximum of 10.

Finding popular, low-difficulty keywords in Organic keywordsFinding popular, low-difficulty keywords in Organic keywords

How to find keywords your competitor ranks for, but you don’t

  1. Go to Competitive Analysis
  2. Enter your domain in the This target doesn’t rank for section
  3. Enter your competitor’s domain in the But these competitors do section
Competitive analysis reportCompetitive analysis report

Hit “Show keyword opportunities,” and you’ll see all the keywords your competitor ranks for, but you don’t.

Content gap reportContent gap report

You can also add a Volume and KD filter to find popular, low-difficulty keywords in this report.

Volume and KD filter in Content gapVolume and KD filter in Content gap

How to find keywords multiple competitors rank for, but you don’t

  1. Go to Competitive Analysis
  2. Enter your domain in the This target doesn’t rank for section
  3. Enter the domains of multiple competitors in the But these competitors do section
Competitive analysis report with multiple competitorsCompetitive analysis report with multiple competitors

You’ll see all the keywords that at least one of these competitors ranks for, but you don’t.

Content gap report with multiple competitorsContent gap report with multiple competitors

You can also narrow the list down to keywords that all competitors rank for. Click on the Competitors’ positions filter and choose All 3 competitors:

Selecting all 3 competitors to see keywords all 3 competitors rank forSelecting all 3 competitors to see keywords all 3 competitors rank for
  1. Go to Ahrefs’ Site Explorer
  2. Enter your competitor’s domain
  3. Go to the Paid keywords report
Paid keywords reportPaid keywords report

This report shows you the keywords your competitors are targeting via Google Ads.

Since your competitor is paying for traffic from these keywords, it may indicate that they’re profitable for them—and could be for you, too.


You know what keywords your competitors are ranking for or bidding on. But what do you do with them? There are basically three options.

1. Create pages to target these keywords

You can only rank for keywords if you have content about them. So, the most straightforward thing you can do for competitors’ keywords you want to rank for is to create pages to target them.

However, before you do this, it’s worth clustering your competitor’s keywords by Parent Topic. This will group keywords that mean the same or similar things so you can target them all with one page.

Here’s how to do that:

  1. Export your competitor’s keywords, either from the Organic Keywords or Content Gap report
  2. Paste them into Keywords Explorer
  3. Click the “Clusters by Parent Topic” tab
Clustering keywords by Parent TopicClustering keywords by Parent Topic

For example, MailChimp ranks for keywords like “what is digital marketing” and “digital marketing definition.” These and many others get clustered under the Parent Topic of “digital marketing” because people searching for them are all looking for the same thing: a definition of digital marketing. You only need to create one page to potentially rank for all these keywords.

Keywords under the cluster of "digital marketing"Keywords under the cluster of "digital marketing"

2. Optimize existing content by filling subtopics

You don’t always need to create new content to rank for competitors’ keywords. Sometimes, you can optimize the content you already have to rank for them.

How do you know which keywords you can do this for? Try this:

  1. Export your competitor’s keywords
  2. Paste them into Keywords Explorer
  3. Click the “Clusters by Parent Topic” tab
  4. Look for Parent Topics you already have content about

For example, if we analyze our competitor, we can see that seven keywords they rank for fall under the Parent Topic of “press release template.”

Our competitor ranks for seven keywords that fall under the "press release template" clusterOur competitor ranks for seven keywords that fall under the "press release template" cluster

If we search our site, we see that we already have a page about this topic.

Site search finds that we already have a blog post on press release templatesSite search finds that we already have a blog post on press release templates

If we click the caret and check the keywords in the cluster, we see keywords like “press release example” and “press release format.”

Keywords under the cluster of "press release template"Keywords under the cluster of "press release template"

To rank for the keywords in the cluster, we can probably optimize the page we already have by adding sections about the subtopics of “press release examples” and “press release format.”

3. Target these keywords with Google Ads

Paid keywords are the simplest—look through the report and see if there are any relevant keywords you might want to target, too.

For example, Mailchimp is bidding for the keyword “how to create a newsletter.”

Mailchimp is bidding for the keyword “how to create a newsletter”Mailchimp is bidding for the keyword “how to create a newsletter”

If you’re ConvertKit, you may also want to target this keyword since it’s relevant.

If you decide to target the same keyword via Google Ads, you can hover over the magnifying glass to see the ads your competitor is using.

Mailchimp's Google Ad for the keyword “how to create a newsletter”Mailchimp's Google Ad for the keyword “how to create a newsletter”

You can also see the landing page your competitor directs ad traffic to under the URL column.

The landing page Mailchimp is directing traffic to for “how to create a newsletter”The landing page Mailchimp is directing traffic to for “how to create a newsletter”

Learn more

Check out more tutorials on how to do competitor keyword analysis:

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Google Confirms Links Are Not That Important




Google confirms that links are not that important anymore

Google’s Gary Illyes confirmed at a recent search marketing conference that Google needs very few links, adding to the growing body of evidence that publishers need to focus on other factors. Gary tweeted confirmation that he indeed say those words.

Background Of Links For Ranking

Links were discovered in the late 1990’s to be a good signal for search engines to use for validating how authoritative a website is and then Google discovered soon after that anchor text could be used to provide semantic signals about what a webpage was about.

One of the most important research papers was Authoritative Sources in a Hyperlinked Environment by Jon M. Kleinberg, published around 1998 (link to research paper at the end of the article). The main discovery of this research paper is that there is too many web pages and there was no objective way to filter search results for quality in order to rank web pages for a subjective idea of relevance.

The author of the research paper discovered that links could be used as an objective filter for authoritativeness.

Kleinberg wrote:


“To provide effective search methods under these conditions, one needs a way to filter, from among a huge collection of relevant pages, a small set of the most “authoritative” or ‘definitive’ ones.”

This is the most influential research paper on links because it kick-started more research on ways to use links beyond as an authority metric but as a subjective metric for relevance.

Objective is something factual. Subjective is something that’s closer to an opinion. The founders of Google discovered how to use the subjective opinions of the Internet as a relevance metric for what to rank in the search results.

What Larry Page and Sergey Brin discovered and shared in their research paper (The Anatomy of a Large-Scale Hypertextual Web Search Engine – link at end of this article) was that it was possible to harness the power of anchor text to determine the subjective opinion of relevance from actual humans. It was essentially crowdsourcing the opinions of millions of website expressed through the link structure between each webpage.

What Did Gary Illyes Say About Links In 2024?

At a recent search conference in Bulgaria, Google’s Gary Illyes made a comment about how Google doesn’t really need that many links and how Google has made links less important.

Patrick Stox tweeted about what he heard at the search conference:

” ‘We need very few links to rank pages… Over the years we’ve made links less important.’ @methode #serpconf2024″

Google’s Gary Illyes tweeted a confirmation of that statement:


“I shouldn’t have said that… I definitely shouldn’t have said that”

Why Links Matter Less

The initial state of anchor text when Google first used links for ranking purposes was absolutely non-spammy, which is why it was so useful. Hyperlinks were primarily used as a way to send traffic from one website to another website.

But by 2004 or 2005 Google was using statistical analysis to detect manipulated links, then around 2004 “powered-by” links in website footers stopped passing anchor text value, and by 2006 links close to the words “advertising” stopped passing link value, links from directories stopped passing ranking value and by 2012 Google deployed a massive link algorithm called Penguin that destroyed the rankings of likely millions of websites, many of which were using guest posting.

The link signal eventually became so bad that Google decided in 2019 to selectively use nofollow links for ranking purposes. Google’s Gary Illyes confirmed that the change to nofollow was made because of the link signal.

Google Explicitly Confirms That Links Matter Less

In 2023 Google’s Gary Illyes shared at a PubCon Austin that links were not even in the top 3 of ranking factors. Then in March 2024, coinciding with the March 2024 Core Algorithm Update, Google updated their spam policies documentation to downplay the importance of links for ranking purposes.

Google March 2024 Core Update: 4 Changes To Link Signal

The documentation previously said:


“Google uses links as an important factor in determining the relevancy of web pages.”

The update to the documentation that mentioned links was updated to remove the word important.

Links are not just listed as just another factor:

“Google uses links as a factor in determining the relevancy of web pages.”

At the beginning of April Google’s John Mueller advised that there are more useful SEO activities to engage on than links.

Mueller explained:

“There are more important things for websites nowadays, and over-focusing on links will often result in you wasting your time doing things that don’t make your website better overall”

Finally, Gary Illyes explicitly said that Google needs very few links to rank webpages and confirmed it.

Why Google Doesn’t Need Links

The reason why Google doesn’t need many links is likely because of the extent of AI and natural language undertanding that Google uses in their algorithms. Google must be highly confident in its algorithm to be able to explicitly say that they don’t need it.

Way back when Google implemented the nofollow into the algorithm there were many link builders who sold comment spam links who continued to lie that comment spam still worked. As someone who started link building at the very beginning of modern SEO (I was the moderator of the link building forum at the #1 SEO forum of that time), I can say with confidence that links have stopped playing much of a role in rankings beginning several years ago, which is why I stopped about five or six years ago.

Read the research papers

Authoritative Sources in a Hyperlinked Environment – Jon M. Kleinberg (PDF)

The Anatomy of a Large-Scale Hypertextual Web Search Engine

Featured Image by Shutterstock/RYO Alexandre


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