Perplexity AI is great at finding information and citing sources. But how you ask makes all the difference.
Think of prompts like restaurant orders.
“Something good” gets you whatever’s left.
“Spicy noodles, extra garlic, no peanuts” gets you exactly what you want.
Same principle, better results.
The magic happens when you add context—what you’re working on, how deep you want to go, or the format you prefer.
- Students build stronger arguments with solid citations
- Researchers surface niche studies faster
- Marketers uncover insights they can actually act on
We’ve rounded up the best Perplexity AI prompts to use right now.
And as a bonus, we’ll look at ClickUp—a fresh, context-aware alternative that brings AI, documentation, and workflow together. 🕵
50+ Perplexity AI Prompts to Try
Summarize this article for me pleaseWhat is Perplexity AI?
Perplexity AI is a conversational search engine powered by large language models (LLMs). It processes natural language queries and returns synthesized answers, citing sources from across the web.
The platform uses artificial intelligence to understand context, which means you can ask follow-up questions and it remembers what you’re talking about. It pulls real-time information, processes it, and presents answers in a readable format with clickable citations so you can verify everything.
What are Perplexity AI prompts?
Perplexity AI prompts are the questions or instructions you type in to get specific answers. The more detail and context you include, the better the response.
A basic prompt like ‘Explain SEO‘ will get you a general overview, but a detailed one like ‘Explain SEO for local businesses with examples of on-page optimization tactics‘ pulls up targeted information that matches what you need.
✅ Example prompt:
“Compare the top 5 email marketing tools for small businesses in 2025. Include pricing tiers, standout features, and one limitation per tool. Present as a comparison table with sources.”
That’s specific, scannable, and directs Perplexity toward structured, verifiable answers.
🧠 Fun Fact: ‘Perplexity’ is actually a statistical measure used to evaluate language models. The lower the perplexity, the better the model predicts text.
Summarize this article for me pleaseHow to Write Effective Perplexity Prompts
Here’s a step-by-step process to create AI prompt templates that deliver useful answers. 👇
Step #1: Define what you need
Before typing anything into the AI tool, figure out what you’re trying to get out of it.
Are you looking for a quick definition, a detailed comparison, statistical data, or step-by-step instructions? Write down your end goal first.
For instance, if you’re a:
- Marketer preparing a campaign pitch, you might need competitor analysis data showing what tactics drove engagement in the last quarter
- Student writing a literature review on climate policy, you need recent research showing how different studies connect
- Content creator fact-checking a claim about user behavior, you need the original source of that statistic
Knowing your objective helps you build a prompt that gets you there in one shot.
🧠 Fun Fact: The term ‘artificial intelligence’ was coined in 1956 during a summer workshop at Dartmouth University. Attendees thought human-level AI could be achieved in a summer. Almost 70 years later, we’re still working on it!
Step #2: Gather the context details
Now collect the specific details that will shape your answer. Think about who will read this information, what industry you’re working in, what time period matters, and the constraints you’re dealing with.
Here’s a checklist of elements you need to consider to become a prompt engineer:
- Target audience or reader level (C-suite executives, college freshmen, hobbyists)
- Industry or niche you’re working in (direct-to-consumer e-commerce, medical devices, indie game development)
- Geographic focus, if it matters (targeting the Australian market, comparing EU vs. US regulations)
- Time period you care about (Q4 2024 data, historical trends since 2010, emerging predictions for 2026)
- Purpose of your research (investor presentation, term paper bibliography, blog post supporting evidence)
The difference this makes is enormous. A content creator asking ‘How are editorial teams at publications like The Washington Post and Reuters using AI tools to speed up fact-checking without sacrificing accuracy, with specific examples of tools and workflows‘ pulls newsroom practices, named tools, and implementation details you can reference or adapt.
Step #3: Choose your output format
Decide how you want Perplexity to present the information.
Do you need a paragraph summary you can drop into a report, a bulleted list for a presentation slide, a comparison table showing pros and cons, or detailed examples with explanations?
Add this to your prompt.
If you’re comparing writing assistant software, ask for a table format: ‘Create a comparison table of ClickUp Brain vs. Jasper vs. Textmetrics covering pricing, keyword database size, and unique features.’
Step #4: Set the depth level
Tell Perplexity how deep you want to go.
Are you looking for a surface-level overview you can read in two minutes, a moderately detailed explanation with some examples, or an exhaustive analysis covering history, current state, controversies, and future implications?
Use specific length or detail indicators. Try ‘Provide a 1000-word explanation of supervised vs unsupervised learning with three real-world examples of each, aimed at someone with basic Python knowledge.’
Being explicit about depth prevents you from sorting through 10 paragraphs when you need two sentences, or getting a shallow overview when you need substance.
🧠 Fun Fact: The idea of human-like intelligence in machines dates back to Talos, the giant bronze automaton from Greek mythology designed to protect Crete. While not an actual machine, the myth portrays Talos with a programmed purpose.
Here’s what his death looked like (apparently):
Step #5: Add your constraints
List any specific requirements or limitations that should filter consistent results. This includes time constraints, geographic focus, source types, or particular angles you want covered.
Examples of useful constraints with real impact:
- ‘Focus on peer-reviewed studies published after January 2023‘ keeps you from citing outdated research
- ‘Include only strategies with documented case studies showing at least 20% improvement‘ filters out theoretical, actionable advice
- ‘Exclude any tactics that require paid advertising budget‘ keeps recommendations realistic for your constraints
These constraints keep results tightly focused on what matters for your project.
📮 ClickUp Insight: While 34% of users operate with complete confidence in AI systems, a slightly larger group (38%) maintains a “trust but verify” approach. A standalone tool that is unfamiliar with your work context often carries a higher risk of generating inaccurate or unsatisfactory responses.
This is why we built ClickUp Brain, the AI that connects your project management, knowledge management, and collaboration across your workspace and integrates third-party tools. Get contextual responses without the toggle tax and experience a 2–3x increase in work efficiency, just like our clients at Seequent.
Step #6: Write your complete prompt
Now combine everything into one clear prompt. Start with your main question, add your context, specify the desired output format and depth, then include any constraints.
A weak prompt looks like: ‘How do companies use customer feedback?‘
A complete prompt looks like: ‘Explain three specific methods that SaaS companies with 1,000 to 10,000 users use to collect and act on customer feedback. Focus on methods that can be implemented with a team of fewer than five people. Present as a numbered list with one real company example for each method, including what tool they used and what result they achieved. Include sources from case studies or interviews published in the last 18 months.’
See the difference? The second prompt will provide you with actionable information, including verified examples that match your company size and resource constraints.
🚀 ClickUp Advantage: Think of ClickUp Docs as your personal prompt library; a space where every Perplexity AI prompt you’ve crafted (and perfected) lives in one place.
You can group them by topic, tag them with use cases, and even track which ones delivered the best results. For example, a content strategist might keep separate pages for research prompts, copywriting templates, and data-backed queries.
It’s a simple way to stay organized, collaborate with your team, and build a reusable bank of AI writing prompts that get results.
Summarize this article for me pleaseTop Perplexity AI Prompts for Different Use Cases
Here’s our curated list of top Perplexity AI prompts for images, research, writing, and a variety of other use cases to get stellar results every time.
Research
- What is the current market size and projected CAGR for [Industry] from 2024-2030 in [Region]? Include market drivers, segment breakdown by [Custom type], and cite reports from Gartner/Forrester/IDC published after 2023. Present as a structured summary with sources
- Compare [Competitor 1], [Competitor 2], [Competitor 3], [Competitor 4], and [Competitor 5] in [Industry]. Create a table showing: pricing, market share with sources, unique features, 2024 product updates, and user ratings from G2/Capterra. Focus on companies serving [Target customer size]
- Identify the top 8 emerging trends in [Industry] for 2025 with at least $10M funding or 100K+ users. For each: explain in 100 words, list three companies using it with specific metrics, and cite adoption data from CB Insights/TechCrunch from Q3 2024 onward. Rank by market impact potential
- Conduct a SWOT analysis for [Company] in [Industry] as of Q4 2024. Include five specific points per quadrant with quantifiable metrics from recent earnings reports, analyst quotes, and 2024 strategic moves. 800-1000 words. Target audience: investment analysts
- How has [Target Demographic] changed their purchasing behavior for [Product Category] between 2022 and 2024 in [Country]? Include: spending shifts (%), preferred channels with engagement data, key purchase drivers ranked, and price sensitivity. Cite 5+ relevant web pages like McKinsey surveys or NRF reports. 300-word summary + detailed sections
- What are enterprise adoption rates for [Technology] in 2023-2024? Include: current adoption %, breakdown by department, specific tools being used, ROI metrics from case studies, adoption barriers, and success factors. Focus on publicly disclosed information from Fortune 500 companies. 1200-1500 words for CTO audience
- Summarize current and pending [Regulation Type] affecting [Company Type] in [Regions] as of October 2024. For each regulation: effective dates, key requirements, penalties, and how [Example Company 1], [Example Company 2], [Example Company 3] adapted. Present as a compliance checklist. Cite official regulatory sources
- Analyze VC funding in [Sector] for 2024. Include: total capital with QoQ comparison, breakdown by stage, top 10 deals with amounts and investors, emerging sub-sectors with specific percentages, and three new unicorn profiles. Focus on US/EU deals over $5M. Use Crunchbase/PitchBook data. 1000-word investment memo format
- What supply chain technologies are [Company Size] manufacturers adopting in 2023-2024? Focus on: IoT, AI forecasting, blockchain, and warehouse automation. For each: adoption %, implementation cost/timeline, efficiency gains with metrics, and 2 case studies. Exclude solutions requiring $5M+ investment. Format as an evaluation guide
- Compare customer satisfaction for [Product 1], [Product 2], [Product 3], [Product 4], [Product 5]. Include: NPS scores, G2/Capterra ratings with review counts, and sentiment analysis from the last six months, showing the top three praises and complaints for each. Filter for [Company Size] reviewers. Present as a decision matrix table with a 200-word summary
- Create an infographic illustrating the market share distribution of [Market/Industry] for the years 2020-2024. Include: pie chart for current market leaders ([Company 1], [Company 2], [Company 3], [Company 4]) with percentages, line graph showing revenue growth trends, bar chart comparing regional performance ([Region 1], [Region 2], [Region 3])
- Create a visual comparison matrix for [Product 1] vs. [Product 2] vs. [Product 3] vs. [Product 4]. Display as a feature comparison table with: product logos at top, 10-12 key features on left side (pricing, [Feature 1], [Feature 2], [Feature 3]), checkmarks/X /X marks or ratings for each. Use a clean, modern design with color coding for better/worse features
🔍 Did You Know? Arthur Samuel published the first paper on machine learning in 1959, titled “Some Studies in Machine Learning Using the Game of Checkers.” It described his program that could learn to play checkers and beat humans. This research popularized the term ‘machine learning.’
Software development
- Write a [Language] function that [Specific Task]. Requirements: handle [Edge Cases], include error handling, follow [Design Pattern], and add type hints/documentation. Also include three test cases covering: success, edge case, failure
- I’m getting [Error Message] when [Action] is performed. Context: using [Tech Stack]. Code: [Snippet]. Analyze root causes specific to this stack, explain the most likely issue, provide debugging steps using [Tools], and supply corrected code with explanations
- Design architecture for [Application Type] supporting: [Requirement 1], [Requirement 2], [Requirement 3]. Include: architecture diagram description, tech stack with justifications, database schema, scaling strategy, and estimated costs on [Cloud Provider]
- Optimize this [Language] code that takes [Current Time] to process [Data Size]: [Snippet]. Goal: reduce to under [Target Time], stay below [Memory Limit]. Provide: profiling breakdown, optimized code, complexity comparison, benchmark results, and explanation of each optimization
- Convert this [Source Tech] code to [Target Tech]: [Snippet]. Maintain functionality while following [Target] best practices. Explain how each [Source] pattern maps to [Target], include type definitions, and provide a migration checklist for similar conversions
- Create an implementation guide for integrating [API Service] into [Framework] application. Cover: setup, authentication with env management, [Feature 1], [Feature 2], error handling, rate limiting compliance, testing approach, and [Compliance Considerations]. Include complete code examples. 2500 words step-by-step tutorial
- Create a test suite for this [Framework] service: [Snippet]. Using [Testing Framework], provide: unit tests with mocked dependencies, integration tests, edge cases, including [Security Test 1], [Security Test 2], [Security Test 3]. Include setup/teardown, aim for 90%+ coverage, follow the AAA pattern. Explain the testing strategy
- Security audit this code: [Snippet]. Check for: SQL injection, XSS, insecure references, authorization/authorization flaws, data exposure, rate limiting, CSRF, file upload issues, weak passwords, and error message leaks. For each, explain the exploit, assess severity using the OWASP scale, and provide secure code. Include a prioritized remediation checklist. 1500 words
💡 Pro Tip: The best-performing AI prompts often mimic human curiosity. It’s a known fact that natural, question-driven prompts yield more nuanced answers. This is why the chain-of-thought prompting technique is popular.
You guide the AI through your reasoning process step-by-step. For instance, write, ‘Let’s think step by step. What factors affect SEO for a new blog, from keyword research to content clustering, and how would you prioritize them for a 3-month plan?’ You’re essentially teaching the AI how to think and not just what to answer.
Marketing
- Create a six-month SEO strategy for [Business Type] targeting [Audience]. Include: 20 keywords with 1,000+ monthly searches, difficulty scores, competition analysis; three content clusters with pillar + supporting posts; content calendar with titles, search intent, traffic estimates. Prioritize keywords with outdated top content (pre-2023). Format as an actionable spreadsheet
- Create three buyer personas for [Product] targeting [Company Size]. Each needs: demographics, psychographics, buying journey with touchpoints, content preferences, objections, and decision authority. Based on: Gartner/Forrester B2B studies from 2024-2025, LinkedIn data, and G2 reviews. Include one real quote per persona. 500 words each + summary table
- Analyze [Competitor]’s content strategy (blog, YouTube, podcast) for the last 12 months. Include: posting frequency, top 10 posts by traffic, format breakdown, topic focus changes, engagement metrics, keyword targets, promotion strategy. Identify five content gaps with 2K+ search volume. Compared to [Competitor 2]. 1500-word intel brief
- What are [Year] B2B SaaS benchmarks for [Channel 1], [Channel 2], [Channel 3], [Channel 4] targeting the enterprise? For each: CTR, conversion rates, CAC, deal cycle, ROAS. Break down by company stage (>$5M ARR). Include the top/bottom quartile. Cite HubSpot/Salesforce/LinkedIn B2B Institute 2024 reports. Present as a reference table + 300-word top performer analysis
- Design an eight-week campaign for [Product Launch]. Goal: [Metric]. Include: email sequence (5 emails with subjects/CTAs), social media calendar, paid ad strategy ($[Budget] across [Platforms]), targeting, content assets with angles, metrics per channel, A/B test hypotheses. Format as brief with timeline and team of [Size]. 2000 words
- Research personalization tactics from [Industry] brands with $100M+ revenue in 2024. Focus on: recommendation engines, dynamic website changes, email personalization, app features, and post-purchase. For each: 2-3 brand examples, tech platforms used, impact on conversion/AOV from case studies, and implementation complexity. Exclude basic tactics. Prioritize 15%+ lift documented. 2000-word playbook with effort/impact matrix
- Design an email header image for [Campaign Name] promoting [Offer]. Dimensions 600x200px. Include: compelling headline text ‘[Headline]’, supporting subtext, relevant imagery ([Product/Lifestyle Scene]), CTA button, brand colors. Mobile-responsive design
- Create a visual content calendar for Q1 2025 showing the [Blog/Social/Email] posting schedule. Grid format with dates, color-coded content types, themes for each week, and major campaign launches highlighted. Clean, organized layout
🔍 Did You Know? The abbreviation ELI5 is a popular way of saying ‘Explain like I’m Five.’ It started as a Reddit community where users asked others to simplify complex topics as if explaining them to a five-year-old. Today, it’s one of the most popular prompt styles in AI tools like Perplexity AI and ChatGPT.
Who knew Michael Scott’s ‘serious query’ would become a question to ask AI?
E-commerce
- Find 10 products in [Category] on Amazon with: 5K-30K monthly searches, competition <40, price [Min]−[Min]- [Min]−[Max], top 10 with <500 reviews, +20% YoY growth. For each: keyword + volume, related terms, top 3 products with revenue estimates, common complaints, profit margin after FBA/COGS (30% assumption), supplier availability (3+ on Alibaba, <500 MOQ). Rank by revenue x entry feasibility
- Analyze pricing for [Product Type] in [Min]−[Min]- [Min]−[Max] range across Amazon, [Retailer], DTC sites in Q4 2024. Include: price clustering points, psychological tactics, price vs rating correlation, marketplace variations, promo frequency/depth (6 months), competitive positioning of [Brand 1-5] by price/features
- Analyze reviews for the top five [Product Category] on Amazon (1,000+ reviews, 2023-2024 only). Extract: most mentioned pros by category, common complaints with %, feature requests, quality issues over time, brand comparisons, and purchase motivations. Provide three quotes per theme. Identify the biggest unmet need in >15% of reviews
- Compile 20 CRO tactics for [Product Category] product pages with A/B test results showing >10% lift. For each: implementation description, psychological principle, documented results, best product categories, and complexity. Exclude >$10K technology investment. Source from Baymard/CXL/VWO case studies. Priority matrix by effort/impact
- Compare Amazon FBA vs 3PL ([Provider 1], [Provider 2]) vs self-fulfillment for [Product Type] with: [X] orders/month, $[Aov], [Weight] lbs, [Dimensions], [% Single Item] orders. For each: cost breakdown, setup costs, breakeven volume, delivery speed, returns handling, international capability, scalability at [Volume 2] and [Volume 3]. Include 2024 pricing and October 2024 FBA fees. Decision matrix with cost per order at volumes. Recommendation based on priorities
- Compare Google Shopping, Meta Ads, and Amazon Sponsored Products for DTC [Category] brands ($[Price Range]). For each: CPC range, conversion benchmarks, ROAS (prospecting/retargeting), CAC:LTV ratio, creative requirements, targeting options, attribution, minimum budget, and learning phase duration. Which to prioritize with $[Budget]/month?
- Generate a before/after comparison image for [Product Benefit]. Split screen showing: left side – problem state with [Issue], right side – solution state with [Product In Use]. Include arrows and labels explaining the transformation. For product page use
- Create a size/dimension guide image for [Product]. Show product with measurements labeled, comparison to a common object for scale, and multiple angle views if needed. Include measurement units in [Cm/Inches]. Clear, technical style with neutral background
Learning and self-education
- Create a 90-day plan from beginner to [Job-Ready Level] in [Skill]. Break into weekly modules with: key concepts per week, daily time ([X] hours/week), resources (free priority, paid <$50), eight progressive projects, bi-weekly checkpoints, common mistakes, and concept dependencies. Target: [Background] with strong self-study
- Explain [Complex Concept] at three levels: (1) ELI5 in 4-5 sentences using analogies for 12-year-olds, no jargon; (2) 300 words for [Prerequisite Knowledge] covering [Key Elements]; (3) 800-word technical dive for [Advanced Audience] with mathematical explanations
- Generate 10 [Skill] practice problems focusing on [Topic], progressing from basic to advanced. Structure: Problems 1-3 (basic), 4-6 (intermediate), 7-8 (advanced), 9-10 (expert). Each includes: realistic scenario, specific question, sample data/schema, expected output, difficulty, concepts tested, common mistakes
- Compare top resources for [Skill] for someone with [Background] aiming to [Goal]: [Resource 1], [Resource 2], [Resource 3], [Resource 4]. Evaluate: teaching approach, depth vs breadth, time commitment, cost, prerequisites, hands-on components, community support, job prep value
- What are the most effective study techniques for [Subject Type]? Include: spaced repetition schedules, active recall methods, and practical application strategies specific to this domain. Provide a weekly study plan for [X] hours/week and tools to use ([Flashcard App], [Practice Platform]). Provide an actionable weekly template
- What prerequisite knowledge is needed before learning [Advanced Topic]? Create a dependency tree showing foundational concepts to master first. For each prerequisite: explanation, why it matters for the advanced topic, recommended learning sequence, time estimate, quality free resources
- Provide five practical projects to apply [Skill] in real-world scenarios. For each include: difficulty level, required knowledge, time estimate, learning outcomes, step-by-step requirements, extension challenges, and how to showcase in a portfolio. Progress from beginner to advanced. Include a proper structure for the starter code and evaluation rubric
🔍 Did You Know? The ‘Turing Test,’ proposed in 1950 by Alan Turing, was designed to see if a machine could carry on a conversation indistinguishable from a human.
Creative writing and content generation
- Generate 10 unique [Genre] story premises combining [Element 1] and [Element 2]. For each: protagonist sketch, central conflict, potential twist. 2-3 sentences per premise. Prioritize originality and emotional hooks
- Create a detailed character profile for [Character type] in [Genre]. Include: backstory, motivations, flaws, strengths, speech patterns, character arc, relationships. Make it three-dimensional and compelling. 800 words
- Brainstorm 20 unique angles for writing about [Topic] targeting [Audience]. Include: contrarian perspectives, personal story angles, data-driven approaches, and innovative formats. Avoid overused angles. Group by content type (how-to, case study, etc.)
- Generate 15 compelling headlines for [Content Type] about [Topic] for [Audience]. Use different formulas: how-to, listicle, question, curiosity gap, benefit-driven. Include character count for each
- Outline [Video Length] video script about [Topic] for [Platform]. Include: hook (first 10 seconds), main points with transitions, engagement tactics, and CTA. Format for teleprompter reading. Target [Audience]. Include timestamp markers
- Rewrite this content in [Specific Tone/Voice] matching the style of [Reference Example]: [Content]. Maintain the core message while adjusting vocabulary, sentence structure, humor level, and formality. Explain five key stylistic choices made and why they fit the target tone
- Write five different opening paragraphs for [Content Type] about [Topic]. Use these techniques: provocative questions, surprising statistics, personal anecdotes, bold contrarian statements, vivid sensory descriptions. Explain the psychological trigger each hook uses
- Design a 10-part content series about [Topic] that builds progressively for [Audience]. Include: episode titles, key takeaways, content formats (video, comprehensive article, infographic, etc), how each piece connects, and optimal publishing cadence. Create a narrative arc that keeps the audience engaged. Include a promotion strategy for each piece
- Generate a book cover design for a [Genre] novel titled ‘[Title]’. Theme: [Mood/Theme]. Include: bold title typography, author name, atmospheric background imagery suggesting [Key Element], color scheme evoking [Emotion]. Style: [Commercial/Literary/Thriller/Romance Conventions]
- Create a character reference sheet for [Character Name] showing: full body view in [Characteristic Pose], close-up of face showing [Key Features], outfit details, color palette, notable items/accessories. Include the brief personality traits listed. Style: [Realistic/Anime/Cartoon/Comic Book]
Summarize this article for me pleaseCommon Mistakes to Avoid with Perplexity AI Prompts
Here are some common mistakes to avoid when working with Perplexity AI prompts:
| Mistake | Solution |
| Asking too many things at once | Focus on one request per prompt to get clear, actionable answers |
| Ignoring word limits | Set clear limits: ‘Explain in under 150 words’ to avoid rambling outputs |
| Asking multiple unrelated questions or not refining prompts at all | Test different angles, tweak wording, and refine based on AI responses |
| Using overly casual language that confuses AI | Keep prompts clear and professional; avoid slang or shorthand unless intended |
| Combining instructions and reference content inconsistently | Use clear sections or tags for instructions vs. source materials |
| Assuming AI understands domain-specific jargon | Add brief definitions or context for technical terms and acronyms |
| Not indicating what to do if relevant information is missing | Direct the AI: ‘If info isn’t found, summarize current consensus or explicitly state ‘none found’’ |
| Assuming the AI ‘remembers’ previous threads or actions | Explicitly restate needed prior context or results in each new prompt |
🧠 Fun Fact: In the early 1980s, a computer at MIT’s AI Lab learned to play Space Invaders using reinforcement learning. The goal was to teach machines how to ‘enjoy’ getting better through feedback.
Summarize this article for me pleaseLimitations of Using Perplexity AI
Many Perplexity AI reviews point out that while the tool performs well for quick lookups, it has several drawbacks. Here are some potential challenges you might face:
- Limited contextual depth or conversational nuance compared with dedicated chatbots; it tends to give concise summaries rather than explore complex ideas in depth
- Source coverage and indexing can be narrower compared to complete real-time web search engines; it may rely on fewer sources and thus miss perspectives
- Citations can sometimes be inaccurate or link to outdated or irrelevant sources, depending on the Perplexity AI prompts you use
- The free version restricts access to specific features like Pro search, file uploads, and higher usage tiers
🔍 Did You Know? The word ‘algorithm’ comes from Al-Khwarizmi, a 9th-century Persian mathematician. He created systematic rules for solving equations.
Summarize this article for me pleasePerplexity AI Alternatives to Explore
Here are our picks for the best Perplexity AI alternatives! 💁
1. ClickUp (Best for context-aware AI assistance and search)
ClickUp is the everything app for work that combines project management, documents, and team communication, all in one platform—accelerated by next-generation AI automation and search.
Where tools like Perplexity answer questions in isolation, the platform’s AI-powered assistant, ClickUp Brain, connects your workspace, documents, and AI insights so your team can ideate, create, and execute content in one place.
Generate ideas that match your goals
ClickUp Brain turns content ideation into a focused, data-backed process.
Suppose you’re refreshing your content calendar for Q1. You ask ClickUp Brain to review existing topics, traffic metrics, and content gaps to propose new themes that align with your SEO and brand tone.
It uses your workspace context to suggest ideas that complement what’s already performing. From there, you can turn each suggestion into a ClickUp Task, tag the relevant owner, and attach reference ClickUp Documents for further research.
📌 Try this prompt: Analyze our current content calendar and generate five new article ideas related to remote collaboration that fill keyword gaps and match our top-performing categories.
Conduct deep research without leaving your workspace
If you’ve used Perplexity AI, you know how quickly it serves up answers. But those answers sit outside your workflow. You still have to copy key insights into a doc, find the right context, and manually turn research into action.
ClickUp Brain MAX changes that. Web Search lets you pull the latest information from trusted sources directly inside ClickUp. You can combine those external findings with your existing projects, Docs, and tasks, making it easy to research, analyze, and act.
Suppose you’re running a content audit and notice your blogs on hybrid teamwork are underperforming.
You prompt it: ‘Search the web for the latest data on hybrid team productivity and list three new insights we should reference when updating our blogs.’
Within seconds, you get recent reports from credible sources (maybe new studies showing hybrid fatigue among remote employees) alongside actionable suggestions for your next rewrite. You can tag your writer, attach the findings to the relevant task, and schedule the update right away.
Turn complex updates into clear next steps
ClickUp Brain also helps you keep large projects moving.
Now, let’s say you ended up with hundreds of flagged pages from your content audit. You ask ClickUp Brain to group pages by issue type (like outdated information or broken links), assign them to the right owners, and set deadlines.
Within minutes, you have a categorized task list mapped to your workflow, complete with checklists for each fix.
📌 Try this prompt: Group all pages flagged during the audit into categories (outdated content, missing links, low engagement) and assign them to respective team members with a two-week deadline.
Bridge creative ideation and execution
When you’re ready to move from idea to output, ClickUp Brain supports you end-to-end. Generate image concepts, build outlines, or even create visual assets using AI art generation inside your ClickUp Whiteboards.
For example, your marketing lead needs a header graphic for a blog on remote teamwork. You ask ClickUp Brain to generate a visual concept aligned with your brand palette. Once approved, you attach the selected image directly to the content task.
ClickUp best features
- Talk it out: Capture ideas on the go and turn spoken thoughts into tasks or notes with ClickUp Talk-to-Text (it’s 4x faster than typing!)
- Use every brain you need: Access ChatGPT, Claude, and Gemini within ClickUp Brain and Brain Max to eliminate AI sprawl
- Search with context: Find answers across tasks, docs, comments, and attachments using ClickUp Deep Search that understands meaning
- Write your way: Create and refine content with ClickUp Brain by entering prompts, editing outputs, and prompt engineering until it fits your tone
- Turn dashboards into insights: Generate standups, reports, and summaries with AI Cards in ClickUp Dashboards that pull real-time context from your workspace
- Stay focused in meetings: Record, transcribe, and summarize discussions automatically with ClickUp AI Notetaker
- Automate with language: Build custom ClickUp Automations and trigger workflows using natural-language prompts
ClickUp limitations
- Its extensive customization features can overwhelm beginners
ClickUp pricing
free forever
Best for individual users
Free Free
Key Features:
60MB Storage
Unlimited Tasks
Unlimited Free Plan Members
unlimited
Best for small teams
$7 $10
Everything in Free +
Unlimited Storage
Unlimited Folders and Spaces
Unlimited Integrations
business
Best for mid-sized teams
$12 $19
Everything in Unlimited +
Google SSO
Unlimited Message History
Unlimited Mind Maps
enterprise
Best for many large teams
Get a custom demo and see how ClickUp aligns with your goals.
Everything in Business +
White Labeling
Conditional Logic in Forms
Subtasks in Multiple Lists
* Prices when billed annually
The world's most complete work AI, starting at $9 per month
ClickUp Brain is a no Brainer. One AI to manage your work, at a fraction of the cost.
ClickUp ratings and reviews
- G2: 4.7/5 (10,585+ reviews)
- Capterra: 4.6/5 (4,500+ reviews)
A Reddit user shares:
2. Google Gemini (Best for multimodal intelligence)
Google’s Gemini works simultaneously across text, images, audio, video, and code. Drop a screenshot of an error message, paste the code, and describe the problem verbally. The AI then processes all three inputs together.
Additionally, Deep Research automates the tedious part of information gathering, browsing hundreds of sites to compile reports while you handle other tasks.
Google Gemini best features
- Build custom Gems that pull from your Google Drive files and automatically reference the latest version when you update those documents
- Use your camera to ask questions about what you see; the tool will show solutions directly on your screen
- Generate short video clips in Vids by describing scenes in natural language to support remote video production
Google Gemini limitations
- Free users hit a five-prompt daily cap for Gemini 2.5 Pro, while Pro subscribers ($20/month) max out at 100 prompts
- Response speed lags noticeably behind competitors when processing the same queries, particularly for complex multi-step tasks
Google Gemini pricing
- Free
- Google AI Pro: $19.99/month
- Google AI Ultra: $249.99/month
Google Gemini ratings and reviews
- G2: 4.4/5 (275+ reviews)
- Capterra: Not enough reviews
📖 Also Read: Best AI Video Generators
3. ChatGPT (Best for dialogue-based research)
ChatGPT search turned the typical ‘type keywords, click links, repeat’ loop into something more fluid. You ask a question in plain language, and the tool automatically searches the web, synthesizing key findings into conversational responses.
The search history function lets you revisit old conversations by keyword, so that the market analysis you did three weeks ago doesn’t vanish into the void. Plus, it integrates DALL-E when you need to generate images within context.
ChatGPT best features
- Activate Deep Research mode to handle multi-step research tasks that read and synthesize content across multiple online sources
- Organize related chats, files, and relevant context under Projects to maintain continuity across multi-session workflows or long-running research topics
- Set up Scheduled Tasks to have ChatGPT proactively perform recurring actions like sending reminders, running analyses, or checking the web for updates
ChatGPT limitations
- Free users face caps of 10-50 GPT-5 messages within five-hour windows before the system switches them to GPT-4
- While the tool doesn’t share your account information, third-party search providers process your queries even after ChatGPT rewrites them, making it a security concern for sensitive information
ChatGPT pricing
- Free
- Go: $5/month
- Plus: $20/month
- Pro: $200/month
- Business: $30/month per user
- Enterprise: Custom pricing
ChatGPT ratings and reviews
- G2: 4.7/5 (1,045+ reviews)
- Capterra: 4.5/5 (260+ reviews)
4. You.com (Best for developer infrastructure)
You.com built its search API specifically for developers who need to ground LLM applications in real-time web data. The platform returns long-form snippets designed for AI consumption rather than the typical metadata tags search engines provide.
ARI (Advanced Research & Insights) scans 400+ sources simultaneously and generates polished reports complete in under five minutes.
You.com best features
- Let it automatically select the optimal model (ChatGPT, Claude, Gemini) for your specific query type
- Create custom search scopes that include your organizational data with Google Drive, OneDrive, and SharePoint integrations
- Create Custom Agents that execute specific instructions repeatedly, eliminating the need to retype the same prompts for routine tasks
You.com limitations
- File upload caps are restricted to 25MB per query on Pro and 50MB on Max, blocking analysis of larger datasets or document collections
- Max plan limits workspace collaborators to 25 users, potentially restricting team expansion as organizations grow
You.com pricing
- Free
- Pro: $20/month
- Max: $200/month
- Enterprise: Custom pricing
You.com ratings and reviews
- G2: Not enough reviews
- Capterra: Not enough reviews
📖 Also Read: What Is Prompt Chaining: Examples, Use Cases & Tools
5. Phind (Best for technical searches)
Phind performs multiple rounds of web searches mid-answer when it needs more information, delivering comprehensive real-time responses instead of limiting itself to one initial query. Answers arrive as diagrams, charts, inline images, cards, and interactive widgets, making complex topics easier to digest.
The platform also generates AI responses with links to online sources like GitHub and Stack Overflow, letting you verify claims quickly.
Phind best features
- Run code in a sandboxed Jupyter environment to test logic, generate matplotlib charts, and attach execution results directly to answers
- Create an answer profile that sets preferences for creative vs. precise responses, plus a user profile to avoid adding repetitive context
- Upload PDFs for summarization, CSVs for data profiling, or images for description and analysis on Pro and Business plans
Phind limitations
- Limited context window compared
- The free version restricts users to 10 searches per day
Phind pricing
- Free
- Pro: $20/month
- Business: $40/month per user
Phind ratings and reviews
- G2: Not enough reviews
- Capterra: Not enough reviews
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