Perplexity AI: What is it and why is it important?

What is Perplexity AI?

Perplexity AI is an AI-powered answer engine. You ask a question in plain language, Perplexity searches the web at that moment, reads the most relevant pages and writes one answer with a numbered citation for each claim. Its own Sonar models and models from OpenAI, Anthropic, Google and others write the answer, but the search step is what sets it apart from a chatbot answering from memory.

Feature	Search engine	AI chatbot from memory	Perplexity
What you get	Links you read and combine yourself	An answer from training data	An answer built from pages found for your question
Sources	You choose what to open	Usually none	A citation per claim
Best for	Finding a specific page	Writing and reasoning on your own text	Research with current, checkable facts
Main risk	Time spent filtering	Invented details	Weak or misread sources presented as fact

Perplexity AI, Inc. was founded in August 2022 in San Francisco by Aravind Srinivas (CEO), Denis Yarats, Johnny Ho and Andy Konwinski, launched its answer engine on 7 December 2022 and was answering 1.5 billion questions a month by May 2026.

How Perplexity AI works: Retrieval-Augmented Generation (RAG)

Perplexity uses Retrieval-Augmented Generation (RAG) to retrieve real-time information: a language model first looks up web pages or documents and then writes its answer from what it found. Every answer goes through four steps:

1. Understanding the question: Perplexity interprets what you ask and splits complex questions into sub-questions.
2. Searching: it searches its own web index and live pages, within the sources you selected.
3. Selecting and reading: it ranks results on relevance, credibility and quality, and reads the passages that fit.
4. Answering: a language model writes the answer from those passages, with a numbered citation for each claim.

The practical consequence is that an answer is never better than the sources Perplexity found and the way the model used them. A vague question leads to the wrong searches, the best source can be missed because of a paywall or a different language, a secondary article can win over the original, and the model can merge two sources into a claim neither of them makes. A citation shows where a sentence came from, not that it is correct.

Which AI models power Perplexity AI?

By default, the Best setting picks a model for each question. Perplexity’s own Sonar is optimised for search: answer quality and user experience, measured through user satisfaction. The February 2025 version is built on Llama 3.3 70B, and Sonar 2 followed in April 2026. On paid plans you can also choose a model yourself; according to Perplexity’s model list of 4 September 2026, the options include GPT-5.6 Terra, Claude Sonnet 5, Gemini 3.7 Flash, Grok 4.6 and Kimi K3, with GPT-5.6 Sol and Claude Opus 5 added on Max.

The model matters less than you might expect, because the sources come from the search step. Leave it on Best and switch deliberately: a reasoning model with Thinking on for analysis, or a second model when an answer feels off. For decisions with real consequences, Model Council (Max and Enterprise Max) runs three models in parallel and shows where they agree and where they differ.

Search, Pro Search, Deep Research or Computer: which mode to use

Mode	What it does	Use it for
Search	One round of searching, a short cited answer in seconds	Facts and quick orientation
Pro Search	Splits the question, searches several times, reads dozens of sources and shows its steps	Comparisons and questions that combine sources
Deep Research	Several rounds across many sources, a report within minutes	Market scans and literature overviews
Computer	An agent that plans, uses your apps and delivers files	Deliverables and recurring reports

A workable rule: start with Pro Search, move to Deep Research when you notice you are asking your fifth follow-up on the same topic, and hand the work to Computer when the result is a document rather than an answer.

How to use Perplexity AI for research: a step-by-step workflow

1. Define the question. Write down which decision it serves and the scope (region, period, sector). “Which CRM fits a 25-person B2B company in the Netherlands?” can be researched; “CRM” cannot.
2. Choose sources and mode. Under Choose sources in the search bar, pick Web, Academic, Social or Finance, and on paid plans your own files or connected apps such as Google Drive or Microsoft 365. Then choose the mode from the table above.
3. Write a question that steers the search. Your question is also the search query, so put the key terms, the period and the type of source in it. The next section shows the difference.
4. Read the answer like an editor. Check which sub-questions Pro Search used and scan the source list. Official sites and original studies are a good sign; vendor blogs and “top 10” articles are a reason to narrow the question.
5. Narrow down and verify. Use follow-ups such as “only sources published after January 2026” or “where do the sources disagree?”, then check the claims your conclusion depends on.
6. Save it in a Project. For research that runs for weeks, a Project keeps sessions, files, standing instructions and preferred web domains together, and you can share it.

Better prompts, better answers: a basic query compared with a structured prompt

Perplexity’s own prompt guide puts it plainly: the text of your question drives the web search, so a specific, descriptive question retrieves better sources.

Basic query: “best CRM software”. This typically returns a general overview based on “best of” articles and vendor pages, with prices and features that may not apply to your country or company size.

Structured prompt: “We are a 25-person B2B services company in the Netherlands looking for a CRM with Outlook integration, EU data storage and a budget under €50 per user per month. Compare HubSpot, Pipedrive, Salesforce Starter and Microsoft Dynamics 365 Sales in a table with price, EU storage, Outlook integration and main limitations. Use the vendors’ pricing pages and reviews from the last 12 months, and mark anything you could not confirm.”

What changes: the search now targets pricing and documentation pages for four named products, the answer becomes a comparable table, recent sources get priority and gaps become visible instead of being filled in. The same logic works for regulation. “AI Act chatbot rules” returns a mixed summary, while a question that names your role (deployer), the use case and the source (“the text of the regulation, with the article per obligation”) produces claims you can check one by one.

Four tips that are specific to Perplexity:

• Put key terms in the question itself. Background instructions shape the answer; the question shapes the search.
• Do not paste example answers. According to Perplexity’s guide, examples can trigger searches for the example instead of your question.
• Do not ask for written-out links. The citations already link every claim.
• Ask in the language of the sources you want, and ask for counter-evidence before you decide.

How to check sources and spot errors in Perplexity answers

In March 2025 the Tow Center for Digital Journalism tested eight AI search tools on identifying news sources: Perplexity scored best and was still wrong in 37% of cases. In October 2025 an EBU and BBC study found a significant issue in around 30% of Perplexity’s news answers, again the lowest of the four assistants tested. Citations make errors easier to find, not less likely. Run this five-point check on every claim you act on:

1. Find the passage. Open the citation, or select a sentence and use Check Sources to see how well the source supports it.
2. Check the date and version. An accurate page from 2024 can make an answer in 2026 wrong.
3. Go to the original. Ask: “What is the original source of this figure?” Secondary reporting often rounds numbers or drops conditions.
4. Judge the type of source. Perplexity’s Government, Academic and Trusted labels rate a website as a whole, not the specific claim.
5. Look for disagreement. Ask where the sources conflict, or put the question to a second model.

An example: a LinkedIn post claims that “75% of European companies use AI agents”. Ask Perplexity for the original source, what exactly was measured and how large the sample was. The original often turns out to be narrower: AI in general rather than agents, large enterprises only, or an older year. If no original turns up, treat the figure as unverified.

Practical use cases

Use case	Mode	Prompt that works	Watch out
Competitor research	Pro Search, then Deep Research	“Map the five largest providers of [service] for SMEs in the Benelux: pricing model, target customers and news from the last six months, with a source per row.”	Company websites show what is sold, not what customers experience
Regulation	Pro Search	Name your role, the use case and ask for the article behind each obligation	Check dates in the official text; no substitute for legal advice
Your own documents	Pro Search with a file	“List all mandatory requirements in the attached tender, with the section number for each.”	Confidential files belong in an Enterprise account
Monitoring a topic	Scheduled Tasks in Computer	“Every Monday, summarise last week’s news on [topic] in five points with sources.”	Uses credits; check sources before you act

Comet and Perplexity Computer

Comet: the Perplexity AI browser

Comet is Perplexity’s free AI browser for Windows, macOS, Android and iOS. Its assistant reads the page you are on, so you can summarise a long report, ask questions about a page, fact-check a selected passage or compare open tabs, and shortcuts such as /tldr turn recurring prompts into commands. The assistant can also act on websites, which led to a lawsuit by Amazon; in August 2026 the Ninth Circuit Court of Appeals vacated the preliminary injunction against Comet.

Perplexity Computer: the agentic layer

Perplexity Computer takes a goal instead of a question. It plans the steps, researches, uses connected apps and delivers a report, spreadsheet, presentation or website. It launched in February 2026, is available on all paid plans and runs on credits, where 100 credits equal one US dollar. Use it when the result is a product, such as a monthly competitor report; for a single question it is slower and more expensive. A polished document also makes errors harder to spot, so check its sources as carefully as in a normal answer.

When Perplexity AI is useful, and when it is not

Situation	Fit	Why
A current topic, market or regulation	Strong	Searches live and cites sources
Comparing products or suppliers	Strong	Tables with sources; check prices yourself
Tracing the original source of a claim	Strong	Follows figures back to reports
Writing, tone of voice, creative work	Moderate	ChatGPT or Claude is often better
Niche topics or paywalled sources	Weak	Leans on secondary sources
Legal, medical or financial decisions	Preparation only	A professional decides
Confidential data on a consumer account	Avoid	Use an Enterprise account

Perplexity AI vs. ChatGPT, Google AI Mode, Copilot and Claude

Almost every AI assistant can search the web, so choose by task. Google AI Overviews and AI Mode suit quick lookups inside Search. ChatGPT and Claude are strongest at writing and reasoning on material you supply. Copilot is the natural starting point for work inside Microsoft 365. Perplexity is built for research where you need to check the sources.

In practice many organisations use two tools side by side: Perplexity for research, and a general assistant or Copilot for writing.

Perplexity AI tiers comparison (2026 pricing)

Plan	Price (USD)	What you get
Free	$0	Cited answers and limited Pro Searches; no model choice
Pro	$20/month ($17 billed annually)	Model choice, Deep Research, files, connectors, premium data, access to Computer
Max	$200/month ($167 billed annually)	Highest limits, Model Council, 10,000 Computer credits per month
Enterprise Pro	$40 per seat/month	SSO, admin controls, data never used for training
Enterprise Max	$325 per seat/month	All models, SCIM, audit logs, 15,000 credits per seat

Free is enough to see whether Perplexity suits the way you work, and Pro is the right choice for daily research. Max only pays off with heavy use of Computer or Model Council, and teams working with company data start at Enterprise Pro. Verified students pay $10 per month for Education Pro, and on the website you can pay in your local currency. Prices as listed on Perplexity’s pricing page in October 2026.

Privacy, data and compliance

On Pro and Max you can opt out of your data being used for AI training; on Enterprise plans data is never used for training and retention is managed centrally. For customer or personal data, an Enterprise account with a data processing agreement is the baseline. In the EU, the AI Act’s transparency rules have applied since 2 August 2026, while the Digital Omnibus moved most high-risk deadlines to December 2027 or later (see our EU AI Act checklist). Public sector organisations should check their own rules first; the Dutch government, for example, does not allow civil servants to use AI tools under consumer terms.

How Perplexity chooses sources: getting your own content cited

Perplexity cites pages in its own index or pages it fetches live. According to its crawler documentation, PerplexityBot builds the index and follows robots.txt. Make sure your robots.txt allows it:

User-agent: PerplexityBot

Allow: /

Then check your firewall or CDN: Cloudflare has blocked AI crawlers by default on new domains since July 2025. Put the answer to a question at the top of the page, keep facts and dates current, and write in your customers’ language. Measure through referral traffic from perplexity.ai in Google Analytics 4 and by asking your customers’ questions in Perplexity yourself. There is no published ranking formula, so none of this guarantees a citation.

Conclusion: getting the most out of Perplexity AI

Perplexity’s value is speed combined with traceability, and you only get it if you steer the search and check the result:

• Match the mode to the question, from Search for facts to Computer for deliverables.
• Put context, scope and source type in the question, and ask for a table with source and date.
• Read the steps and sources before the conclusion, and verify the claims you act on.
• Keep confidential data in an Enterprise environment.

Want to inspire your team first? Have a look at the Perplexity Live Demo. The Perplexity AI Workshop teaches your team the research workflow from this article, and our Perplexity consultancy service helps you implement Perplexity in your organization.

Frequently asked questions about Perplexity AI (FAQ)