Perplexity AI reimagines the search engine with AI. Instead of a list of links, you get a direct, synthesized answer with numbered source citations — so you can verify every claim. It is the best AI tool for research, fact-checking, and staying informed.
Unlike ChatGPT and Claude which can confidently state incorrect facts, Perplexity cites every claim with numbered source links. You can click any citation to verify the original source. This makes it ideal for research where accuracy matters.
Perplexity searches the web on every single query — not just when it thinks it needs to. This means you always get current information, even for queries where other AI tools would rely on potentially outdated training data.
Click Deep Research and Perplexity autonomously runs 20-30 web searches, synthesizes results from multiple sources, and produces a comprehensive multi-source report with an executive summary and detailed findings — in 3-5 minutes.
Use Focus modes to search within specific sources: Academic (peer-reviewed papers via Semantic Scholar), YouTube (video content), Reddit (community discussions), News (current events), and Wolfram Alpha (mathematical and scientific calculations).
Unlike a standard search engine, Perplexity maintains conversation context. You can ask follow-up questions like 'Tell me more about the third point' or 'How does that compare to the approach used by [competitor]?' and it understands the context of your previous questions.
Create shared research workspaces where teams can collaborate on research topics. Upload documents, set AI instructions, and let multiple users ask questions about the same research context — useful for research teams and competitive intelligence.
Open perplexity.ai in any browser. No account needed — start searching immediately. Create a free account to save your research history and get 5 Deep Research queries per day.
Free plan: unlimited standard searches with cited sources, 5 Deep Research queries per day, all Focus modes, and mobile apps. Pro ($20/mo): unlimited Deep Research, higher-quality models, and image upload.
The interface is a single search bar. Below it: Focus selector (choose your source type) and a Pro toggle for Deep Research. Start with a simple factual query to see how citations work before doing complex research.
Perplexity is a research engine, not a chatbot. Query quality directly determines answer quality.
Weak query: Tell me about AI.
Strong query: What are the most significant large language model releases from January to May 2026? For each: model name, company, key technical improvement over the previous version, benchmark scores where available, and pricing changes. Focus on text and reasoning models, not image generators. Only include announced or released models — not rumors.
Rules for better queries: use complete sentences, specify time periods, state what data format you need, define what to exclude, and specify your audience if technical level matters.
Every claim in a Perplexity answer has a bracketed number citation [1][2][3]. This is what fundamentally differentiates Perplexity from ChatGPT or Claude.
Verification workflow:
1. Read the full answer first without clicking anything
2. Identify the 2-3 most critical facts — numbers, quotes, specific claims
3. Click those citation numbers and skim the source page to confirm accuracy
4. Check the publication date of each source — old sources can give outdated answers
Important: Perplexity occasionally misrepresents sources, uses outdated pages, or cites sources that only tangentially support the claim. Always verify high-stakes figures before using them in presentations or reports.
Toggle on Deep Research before typing. Write your question as a specific research brief — the more precise, the better the report:
Comprehensive competitive landscape analysis of the B2B project management software market as of May 2026. Include: the 6 largest players by market share or ARR, their pricing and target segment, key product differentiators, recent product updates or funding news in the last 6 months, and analyst commentary or user sentiment from reviews. Focus on tools used by engineering and product teams (50-500 employees).
Wait 3-5 minutes. Perplexity autonomously runs 20-30 web searches, reads each source, and synthesizes a structured 1,500-3,000 word report with full citations. Save it using the Share button.
Click the Focus dropdown before your query to restrict sources:
Academic: Searches peer-reviewed papers and scientific publications. Use for: medical information, scientific claims, research-backed arguments. Example: What does peer-reviewed research from 2023-2026 say about the effectiveness of exercise timing on sleep quality? Include study sizes and effect sizes.
News: Focuses on recent reporting. Use for: company announcements, market events, current developments. Add a time frame: in the last 7 days.
YouTube: Searches video transcripts. Use for: expert opinions, tutorials, conference talks. Example: What are the top 3 frameworks for building production-ready RAG systems according to recent technical YouTube talks?
Wolfram Alpha: Mathematical and computational queries. Use for: financial calculations, unit conversions, statistical formulas.
Perplexity retains context within a conversation thread. After your initial Deep Research report, dig deeper:
After a competitive landscape report on project management tools:
Go deeper on Linear specifically. What is their current pricing for teams above 50 users? What enterprise features did they add in the last 6 months? What are the most common criticisms from users on G2, Capterra, or Reddit in 2026?
Each follow-up triggers additional focused searches. Chain 4-6 follow-ups to build a comprehensive multi-layer research document that would take hours to assemble manually.
Use Share to get a shareable URL of your full research thread — pass it to colleagues who can read all questions, answers, and sources in sequence.