Last Updated: March 3, 2026

Most AI marketing tools help only if they are tied to clear goals like more leads, faster content, or lower ad costs, not just curiosity.
In 2026, you need a small stack that covers research, content, visuals, SEO, and customer conversations, instead of ten overlapping apps.
General AI assistants like Gemini or ChatGPT are great, but you get real leverage when you pair them with focused tools such as Ahrefs or Canva’s Magic Studio.
The safest way to test AI is a 60-90 day experiment with specific metrics, guardrails for data and brand, and a clear decision to scale up or shut it down.

AI marketing tools can save you dozens of hours a month, but only if you stop chasing every shiny launch and pick tools that fit how you actually work.

Here I will walk through the 7 tools that keep showing up in real campaigns this year, how they stack up, when they are the wrong choice, and a simple way to plug them into your existing workflow without breaking it.

Key AI Marketing Trends In 2026 That Shape This List

A lot changed in a short time, and if you still think of AI as a cute chatbot that writes headlines, you are behind.

Right now, most serious teams are doing three things with AI: compressing production time, connecting tools that never talked before, and pushing more experiments into the same budget.

Suite-first, not tool-first: HubSpot, Salesforce, Klaviyo, and Google Ads now ship built-in AI, so your stack needs to work with them, not fight them.
Multimodal campaigns: One brief turns into copy, images, and video variations in a single flow, instead of three separate projects.
First-party data focus: Teams are feeding CRM, analytics, and support transcripts into AI, while trying hard not to leak personal data into open systems.
AI copilots instead of dashboards: Marketers ask questions in plain language inside ad platforms, email tools, or docs, and get ready-made actions, not just charts.

This list reflects that reality, so you will see fewer older niche tools and more that fit across channels or go much deeper on one critical function.

How I Chose These Tools (And What I Left Out)

I did not try to catalog every AI app on Product Hunt, because that would waste your time.

Instead, I focused on tools that plug into real marketing workflows across research, SEO, content, creative, and customer touchpoints.

Kept: Tools that either sit at the center of a workflow (like Gemini Advanced or Ahrefs) or are clearly better than older options in their category.
Replaced: Lightweight visual tools such as Designs.ai and Lumen5 that fell behind Canva’s Magic Studio and newer video models.
Skipped as stand-alone picks: ChatGPT, Claude, and Microsoft Copilot are great general assistants, but here I tie them into the tools where they add the most value instead of repeating yet another generic review.

If you already use ChatGPT or Claude, you will still find spots where they slot into these flows without needing to rebuild your whole stack.

Quick Comparison Table

Tool	Main Role	Best For	Typical Starting Price	Main Drawback
Gemini Advanced (Google)	General AI copilot	Daily marketing tasks, content, analysis	Around $20 per month	Needs clear prompts and human review
Ahrefs AI Suite	SEO & content strategy	Organic search growth, competitor research	Around $99 per month	Price climbs as you add projects/users
Perplexity AI Pro	Research & fact-finding	Market research, outlines, competitor checks	Roughly $20 per month	Can push you toward sources that share the same bias
Canva Magic Studio	Design & light video	Social graphics, ads, simple videos	Around $15 per user per month	Advanced brands may outgrow template look
Midjourney / Stable Diffusion	Custom marketing imagery	Original visuals, concepts, ad creatives	Varies, often under $30 per month	Prompting takes practice, usage rights can be tricky
Runway or Pika	AI video generation	Short promos, concept videos, social clips	Roughly $15-$35 per month	Not ideal for long-form, needs editing polish
Manychat	Chatbot & messaging funnels	Lead capture, DMs, broadcast promos	From around $15 per month	Easy to cross the line into spam if you are careless

Pricing shifts a lot in this space, so treat those numbers as ballpark and always double-check current plans before you budget around them.

AI Safeguards Marketers Should Use In 2026

Before we get into each tool, it is worth setting one thing straight: AI can create real problems if you treat it like a magic box.

Smart teams protect themselves with simple rules instead of hoping nothing goes wrong.

If you would not email a raw spreadsheet of customer data to a stranger, do not paste it into a public AI tool.

Data privacy: Keep personal data, private pricing, and unreleased campaigns out of consumer tools, and use enterprise plans or self-hosted options when legal or security risk is high.
Brand safety: Every AI draft needs a human pass for tone, claims, legal risk, and cultural context, even if it looks polished at first glance.
Regulated niches: If you work in finance, health, or legal, build a checklist for claims, citations, and compliance review before anything hits ads or email.

This might feel like it slows you down for a week or two, but the first time an AI hallucinates a discount you never offered, you will be glad you had that extra layer.

Isometric illustration of a compact AI marketing stack with goals and guardrails. — A focused AI stack driving real marketing outcomes.

1. Gemini Advanced: Your General Marketing Copilot

Gemini Advanced is still one of the best all-round AI tools for marketers who live inside Google products and need help with a bit of everything.

If you already depend on Docs, Sheets, Drive, and Google Ads, it tends to feel like a natural extension rather than yet another tab.

What Gemini Does Well For Marketers

Newer Gemini models like the 1.5 family brought longer context and better multimodal support, which sounds technical but has a direct impact on daily work.

You can drop long briefs, multi-tab spreadsheets, and full emails into a single chat and still get coherent output instead of surface-level blurbs.

Draft email sequences, landing pages, and ad variations from one clear brief, then refine through a fast back-and-forth.
Summarize long analytics exports or survey responses into key patterns and follow-up questions.
Feed in performance data from Google Ads or Performance Max reports and ask for ideas to test next.
Work with screenshots, creative assets, or rough wireframes in the same conversation.

This feels closer to a junior strategist than just a writing bot, if you give it enough context.

Where Gemini Fits Against ChatGPT, Claude, And Copilot

I do not think one general assistant wins everywhere, which some people hate to hear, but it is true in real projects.

Gemini tends to shine if your world is already Google, while ChatGPT and Claude sometimes win on raw writing feel or niche plugins.

Tool	Best Use For Marketers	Watch Out For
Gemini Advanced	Docs/Sheets workflows, Google Ads help, mixed media briefs	Can oversimplify if your prompt is vague
ChatGPT (paid)	Content drafts, custom GPTs, plugin-heavy tasks	Facts still need checks, models vary by plan
Claude	Long-form strategy docs, complex research summaries	May feel too cautious or verbose for ad copy
Microsoft Copilot	Teams/Office users, PowerPoint and Excel-heavy work	Less helpful if you are not deep in Microsoft tools

For many marketing teams, the right move is boring: pick the one that integrates best with your current stack, then learn it well instead of hopping constantly.

Practical Gemini Use Cases

To make this less abstract, here is how a small ecommerce brand I advised used Gemini over 30 days.

They did not try anything fancy, just focused on the bottlenecks that annoyed them most.

Turn past support chats into a proper FAQ article that cut repeat tickets by around 18 percent.
Draft three email promo angles each week, which the founder then edited instead of starting from scratch.
Rewrite bulky product descriptions into shorter, mobile-friendly versions aligned with their tone.
Outline ad creative tests based on the previous month of Google Ads search term data.

Lazy prompts give lazy answers; if you catch yourself typing “Write me an ad” with no context, you are wasting your subscription.

I usually tell teams to write prompts like a mini creative brief: audience, offer, channel, past results, and what change you want this asset to produce.

Limitations And When Gemini Is Not Enough

Gemini still hallucinates or glosses over details sometimes, and I think some marketers underestimate that risk.

You should double-check stats, legal claims, and anything that touches pricing or guarantees, even if the output sounds confident.

If you need deep SEO content scoring or link analysis, Gemini alone is not enough; pair it with Ahrefs or a similar suite.
If your job is very Microsoft-centric, Copilot may be less friction day to day.
If you write long, nuanced thought pieces, Claude often feels closer to a careful human editor.

Gemini is your generalist; the rest of this list covers the specialists that sit around it.

Visualizing how Gemini compares to other AI copilots.

2. Ahrefs AI Suite: SEO And Content Strategy With Teeth

Ahrefs has always been strong for backlinks and keyword research, but its newer AI features make it much more of a day-to-day content partner.

If organic traffic is a core growth channel for you or your clients, this is usually where I tell people to spend serious budget instead of yet another content tool.

Key AI Features That Matter In 2026

The nice thing with Ahrefs AI is that it sits on top of a big pool of real search data, so its suggestions are not just vibes.

That does not mean it is perfect, but at least it is opinionated in a useful way.

AI content gap reports: For a target keyword, it surfaces subtopics and questions your page misses compared to top results.
Title and meta suggestions: It drafts variants that balance keyword coverage and click appeal, which you can test against your current ones.
Internal linking ideas: It scans your site and suggests hubs and cross-links that spread authority across related pages.
AI-assisted site audits: It turns dry technical reports into a prioritized list, with plain-language tasks for dev and content teams.

On a SaaS client, one AI content gap run for a single keyword yielded 12 missing subtopics, and fixing just three of them moved that page from page two to the middle of page one within a couple of months.

Ahrefs AI vs Other SEO AI Tools

I do not think Ahrefs is the only choice, and if someone tells you that, they are probably not testing enough.

There are good reasons to consider SurferSEO or MarketMuse alongside it.

Tool	Strength	Best For
Ahrefs AI Suite	Backlinks, competitor research, full-site context	Sites that need both technical and content insights
SurferSEO	On-page content scoring and brief generation	Content teams pushing lots of SEO articles monthly
MarketMuse	Topic modeling and authority mapping	Brands building deep topical hubs over time

I still lean toward Ahrefs as the first buy, then pull in Surfer or a similar tool if you need more granular content scoring later.

How To Use Ahrefs AI In A Real Content Workflow

Here is a simple playbook that has worked well for content-led B2B companies.

It is not fancy, but it beats guessing.

Start with a small group of business-critical topics and run AI content gap reports for each.
Ask the AI to suggest 5-10 article or guide ideas that cover the gaps and map to different funnel stages.
Export those into your content calendar, then pull structured briefs into Gemini or ChatGPT for first-draft writing.
After publishing, use Ahrefs to track ranking shifts and ask the AI which articles to expand, interlink, or retire.

The worst use of SEO AI is letting it write your article from scratch; the best use is letting it tell you what not to waste time on.

When I see a site stuck on a plateau, it is often because they keep publishing variations of the same idea instead of following a data-backed map like this.

When Ahrefs Is Overkill

If you run a very small site or most of your traffic comes from paid social, you might not get full value from Ahrefs right away.

In that case, starting with a lighter tool or focusing on one Ahrefs project at a time can keep costs under control.

Low-competition local businesses might get enough SEO traction with basic keyword tools paired with good content.
If most of your sales come from email or influencers, weigh Ahrefs against investing in better creative first.

I still like having at least one serious SEO tool across the company, but it does not always need to sit on every single project line from day one.

3. Perplexity AI: Fast, Cited Research For Marketers

Perplexity AI is not a writing tool first; it is more like giving your research process jet fuel, which many marketers underestimate.

If you are tired of skimming ten tabs of vague blog posts just to plan one campaign, this is often the missing piece.

Why Perplexity Feels Different From Generic Chatbots

The main value is that it shows where its answers come from and keeps pulling in fresh web results.

You get citations, links, and a path to double-check any claim instead of trusting a black box.

Scan competitor messaging quickly: homepages, pricing pages, and feature pages distilled into bullet notes.
Pull market size estimates, trend summaries, and recent news with links to original sources.
Gather product review themes from across sites to see what customers praise or complain about most.
Draft brief outlines that include real quotes or stats you can later verify and format.

Is it perfect? No, and sometimes it leans too heavily on a small set of sources, but that is still better than a hallucinated answer that looks real.

How Perplexity Fits With Gemini Or ChatGPT

You can think of Perplexity as your research front-end and Gemini or ChatGPT as your writing backend.

This split keeps your process clearer and your drafts better grounded.

Use Perplexity to gather facts, quotes, and competitor angles on a topic.
Save or export key findings, along with source links and any charts or tables.
Feed that into Gemini or another model with a prompt that explains the audience, goal, and constraints.
Ask for a draft that references your research rather than making up new stats.

If your draft has no links back to real sources, assume at least part of it is wrong until you prove otherwise.

Once you get used to this two-tool loop, it is hard to go back to guessing or writing without a research pass.

Limits To Watch Out For

Perplexity can pull you toward whatever is already well indexed and written about, which sometimes biases your thinking toward the consensus.

When you work on a fresh niche or early category, you still need direct user research and interviews, not just smarter search.

Use it as a first pass, not a replacement for talking to customers or reviewing your own analytics.
Watch how often it cites the same few sites; if that pattern shows up, dig beyond them on your own.

This is one of those tools that feel almost too helpful, but you still control where your insights come from and how deep you go.

Flowchart showing AI-assisted SEO process from research to content optimization. — How an AI suite structures modern SEO work.

4. Canva Magic Studio: Design And Light Video For Non-Designers

Canva moved far beyond simple templates and now ships Magic Studio, which pulls AI across images, layouts, and video edits.

For many marketing teams, it quietly replaced older tools like Designs.ai because it covers more ground with a friendlier interface.

Where Canva Magic Studio Helps Most

If you handle social content, ads, or basic explainer videos without a full design team, Canva probably sits open on your screen already.

The newer AI pieces just cut more of the boring work.

Magic Design: Upload a brief or asset, and it generates ready-to-edit layouts for carousels, ads, and thumbnails.
Text to image: Quickly create on-brand visual concepts when stock photos feel stale.
Magic Edit & Erase: Fix or tweak parts of an image instead of redoing the whole thing.
Video tools: Trim, caption, and resize short clips for Reels, Shorts, and TikTok without a full editor.

One small ecommerce founder I spoke with cut weekly asset creation from roughly 5 hours to under 90 minutes just by standardizing everything inside Canva with a few Magic Studio features.

Canva Magic Studio vs Designs.ai And Adobe Express

Designs.ai still works, but most marketers I see switching now go toward Canva or Adobe Express.

The reason is simple: better templates, more active updates, and stronger ecosystems.

Tool	Strength For Marketers	Where It Falls Short
Canva Magic Studio	All-in-one quick design, social, and basic video	Can look template-heavy if not customized
Designs.ai	Logo kits, bulk simple creatives	Feels limited next to Canva’s pace of updates
Adobe Express	Closer tie-in with Adobe pro tools	Overkill if you do not use Adobe elsewhere

I would not keep paying for a smaller tool in this category unless it delivers something Canva truly cannot, such as a key integration or API for your stack.

Practical Canva Workflow For Campaigns

Here is a lightweight process I often share with small teams who need more content without more headcount.

No fancy systems, just consistent habits.

Set up brand kits with colors, fonts, and logo variants, so AI-generated designs stay closer to your look.
For each campaign, ask Magic Design to propose layouts for 3-5 formats: one paid ad, one organic post, one story, one email header.
Use Magic Edit to adapt a base visual for different audiences or offers instead of designing from zero each time.
Turn your best post into a short video with text overlays and music for extra reach.

It will not replace a senior designer, but it frees that person to work on complex pieces while marketing handles day-to-day assets.

5. Midjourney & Stable Diffusion: Original Visuals That Stand Out

Midjourney and Stable Diffusion 3 changed what is realistic for small teams that want unique visuals without big photo budgets.

They are more demanding than Canva, but when you get comfortable, the creative range is hard to match.

When These Tools Make Sense

If your brand needs distinctive imagery, not just slightly better stock, these models are worth the effort.

I see them used heavily in concept art, high-impact hero images, and ad creative variations.

Generate mood boards or concept lines for a new brand or campaign before any photoshoot.
Create surreal or stylized visuals that would be too expensive to shoot in real life.
Test multiple visual angles for ads and see what drives higher click-through before investing in full production.

Stable Diffusion variants, especially when self-hosted or on controlled platforms, can also be tuned more tightly to your brand style, though that adds setup work.

Prompting And Control

The catch is that these tools are far less forgiving of vague prompts than something like Canva or Gemini.

You refine through iteration, which some people enjoy and others find painful.

Think of prompts as directing a photoshoot: if you just say “make it nice,” do not be surprised when the results feel random.

Start with clear descriptions of subject, style, lighting, and use case.
Save prompts that work and adjust only small parts per run, like color or framing.
Keep a library of outputs that performed well and reverse-engineer what looked and felt right.

After a month or two, your prompts often read like a custom language, and that is fine if it drives better creative tests.

Legal And Brand Considerations

This part gets less attention than it should, but it matters, especially for bigger brands.

You need to think about training data, likeness, and how comfortable your legal team is with current guidance.

Avoid prompts that mention living people or clear trademarks.
Check your platform’s terms for commercial use and attribution rules.
When in doubt, run a quick legal review for flagship campaigns instead of only looking at the art.

Some companies choose to keep heavy use of these models for internal concepts and rely on traditional production for final public assets, which is a valid middle ground.

Infographic comparing Canva-style AI design with advanced generative image tools. — Infographic of key AI design and imagery tools.

6. Runway & Pika: Modern AI Video For Marketers

Short video is still one of the fastest ways to gain reach, but traditional editing can be slow and expensive.

Runway and Pika give you a middle option between full productions and basic slideshow tools.

What These Video Tools Actually Do Well

I see some people hype them way beyond reality, and that does not help anyone.

They are not Hollywood replacements, but they are strong for concepting and simple marketing clips.

Turn text prompts into short, visually rich clips for teasers or backgrounds.
Extend or modify existing footage, like changing environments or styles around a product.
Create A/B variations of intros or hooks to test engagement in Reels or ads.

One brand I worked with used Runway to concept three visual directions for a product launch video; they then shot a lean live-action version, but the early AI clips helped align everyone faster.

When They Beat Tools Like Lumen5

Lumen5 still has value for simple text-to-video slideshows, but it does not compete with the creative control of newer generators.

If your goal is scroll-stopping visuals rather than narrated blog posts, Runway or Pika are usually a better bet.

Use Case	Old Approach	AI Video Approach
Concept video for new campaign	Storyboard + rough edit in standard software	Text prompts in Runway/Pika for concept clips
Quick social teaser	Manual editing, stock footage search	Generate short stylized clips to overlay text
Variant ad hooks	Expensive reshoots or heavy edit rounds	AI-modified versions of the same base asset

This does not remove the need for human editing; most of the time you still want a person to pick shots, tweak pacing, and keep your brand consistent.

Limitations You Should Expect

These models struggle with long-form structure, detailed text on screen, and certain fine motions.

Expect some weird frames and artifacts, especially on early prompts.

Use clips as segments in an edited sequence instead of trying to get a full 60-second spot in one go.
Plan on manual captioning or overlays for clarity, even if the model adds some text.
Keep a tighter review loop for anything that might misrepresent your product or show odd body shapes.

If you go in with realistic expectations, they add meaningful speed and variety; if you expect fully polished TV spots, you will walk away annoyed.

7. Manychat: AI-Assisted Messaging Funnels That Do Not Feel Spammy

Manychat remains one of the best ways to run structured conversations on channels like Instagram DMs, Facebook Messenger, and WhatsApp.

The trick is to treat it as a guided flow with AI assists, not as a robot trying to replace humans for everything.

Channel Support And Integrations In 2026

The platform evolved with Meta’s policies and the rise of WhatsApp, which matters a lot if you run global campaigns.

You now get a more complete messaging stack in one place.

Instagram DMs and story replies with keyword or tap triggers.
Facebook Messenger flows for quizzes, lead capture, and FAQs.
WhatsApp messaging for opt-in updates, reminders, and order checks.
Bridges to email and SMS tools so you can move leads into deeper sequences.

AI helps with intent detection and flexible replies, but you still design the core logic of the flows.

Compliance And Best Practices

This is where many marketers go wrong and blame the tool when the real problem is their own aggressive settings.

Meta’s rules on promotional messaging windows and opt-ins are strict for a reason.

If your bot sends more messages than you would personally tolerate as a user, you are heading toward trouble from both Meta and your audience.

Make opt-ins clear, and do not hide them behind confusing wording.
Respect 24-hour messaging windows and limit promotional blasts.
Test frequency and tone by actually going through your own flows as a user.

The goal is to feel like a helpful assistant, not a late-night spammer with your logo attached.

Practical Manychat Use Cases

I like to start with small, very focused flows and then layer on complexity, instead of trying to automate everything in one go.

Here are a few patterns that keep working.

Lead magnet delivery: “Comment X” on a post triggers a DM with the promised resource and a short qualifier flow.
Product finders: Simple quizzes that route users to the right product page and capture contact info.
Launch reminders: Opt-in lists for restocks, drops, or webinars, tied into email or SMS.

When you mix this with AI-generated scripts and Gemini-based analysis of chat logs, you start to see patterns in objections and wording that can feed back into your ads and landing pages.

AI Agents And Integrated Workflows: Where Things Are Heading

One of the biggest shifts lately is toward AI agents that chain multiple steps without you nudging them each time.

These are not toys anymore, but I still think some marketers underestimate the setup they need.

Research agents that pull info from Perplexity, your CRM, and analytics to draft campaign briefs.
Content agents that turn a single seed idea into outlines, drafts, and social variations, then push them into tools like Canva or your scheduler.
Support agents that learn from Manychat or Intercom tickets, then propose updated FAQs, macros, and even ad angles based on common questions.

You can build pieces of this with custom GPTs, Zapier, Make, or native automation inside your core tools, but you still need a human to own quality, logic, and goals.

I have seen teams try to go fully hands-off and fail badly because the agent chased activity, not outcomes.

Checklist infographic summarizing AI video tools and messaging funnel best practices. — Key checks for AI video and conversational funnels.

How To Measure ROI On AI Marketing Tools

If you do not define success ahead of time, every AI subscription feels useful for two weeks and then turns into background noise.

A simple measurement plan keeps you honest and protects your budget.

Time saved: Track how long common tasks take before and after, like drafting a newsletter or producing a social batch.
Output volume: Measure assets per week or month per channel without quality slipping.
Performance metrics: Watch CTR, CPC, revenue per email, or organic traffic for specific campaigns that used AI help.
Error rate and rework: Count how often AI outputs cause mistakes, confusion, or re-dos.

If a tool does not clearly save time or improve results within 90 days, you should question whether it deserves a spot in your stack.

I usually suggest a 60-90 day test where you pick one or two metrics per tool and decide in advance what counts as a pass.

That way, you do not keep paying just because it feels wrong to cancel something you barely use.

Sample AI Stacks For Different Team Sizes

One mistake I see often is solo founders copying the stacks of large agencies, which just creates overwhelm.

Match your stack size to your team and channels instead.

Solo Founder Or Very Small Team

General copilot: Gemini Advanced or ChatGPT for daily writing, planning, and analysis.
SEO/core research: Perplexity AI plus a lightweight SEO tool if budget is tight, or Ahrefs if search is central.
Creative: Canva Magic Studio for graphics and simple video, with Midjourney for key visuals if needed.

This stack keeps seat count and complexity low, while still covering the main marketing tasks most small businesses handle.

In-House Marketing Team

General copilot: Gemini for Google-centric teams, or a mix of ChatGPT and Claude where needed.
SEO suite: Ahrefs AI as the backbone for planning and audits.
Research: Perplexity for fast market and competitor checks.
Creative: Canva Magic Studio plus Midjourney or Stable Diffusion for original campaigns.
Video: Runway or Pika for concept videos and short social clips.
Messaging: Manychat or a native AI chat solution tied into support and sales.

The key here is to assign ownership, so each tool has a primary person who keeps prompts, templates, and workflows clean.

Agency Or Multi-Brand Team

Multi-tenant SEO: Ahrefs AI Suite across clients, plus maybe Surfer for content-heavy accounts.
General AI: Shared prompt libraries on Gemini or ChatGPT, with clear rules on client data.
Creative engine: Canva or Adobe Express for day-to-day work, plus Midjourney/Stable Diffusion for custom campaigns.
Video: Runway or Pika for quick concepts, paired with traditional editing tools for final output.
Chat and lead capture: Manychat across Messenger, Instagram, and WhatsApp where allowed.

Agencies should be stricter with AI governance, because one careless prompt with client data can damage multiple relationships at once.

Putting It All Together In A Simple Playbook

Let me give you one straightforward example of how these tools can work together on a content-led campaign.

It is not the only way to do it, but it is a solid reference point.

Use Perplexity and Ahrefs AI to map the topic, find gaps, and pick target keywords.
Draft outlines and articles with Gemini or ChatGPT, grounded in that research.
Convert key articles into short Runway or Pika clips, plus Canva-based graphics for social posts and email banners.
Generate supporting visuals with Midjourney or Stable Diffusion where stock images fall short.
Set up Manychat flows tied to those campaigns for lead capture and FAQs, then feed chat insights back into your content.

Is this perfect? No, and you will probably adjust it to your channels and brand, but it gives you a clean track to run on instead of treating each tool as its own side project.

If you stay honest about ROI, keep guardrails around data and brand, and resist the urge to chase every new launch, a lean AI stack like this can quietly become one of the highest-leverage parts of your marketing engine.

Need a quick summary of this article? Choose your favorite AI tool below:

🤖 Summarize with ChatGPT 🔍 Summarize with Perplexity 💡 Summarize with Claude