Perplexity AI

Perplexity AI occupies a category that did not really exist before it: an AI answer engine that behaves like a search engine but responds like a knowledgeable assistant. Rather than returning links, it reads the web in real time and synthesises an answer with inline citations so users can verify every claim. For research, fact-checking, and quickly understanding unfamiliar topics, this approach has clear advantages over both traditional search and standalone AI assistants working from outdated training data.

Founded in 2022 by Aravind Srinivas along with alumni from OpenAI and Google DeepMind, Perplexity has grown quickly and attracted significant investment, positioning itself as a credible long-term challenger to traditional search.

The free plan gives basic search with standard models and five Pro searches per day. Pro searches use more capable models, support file uploads, and perform multi-step web research. The Pro subscription at $20/month unlocks unlimited Pro searches, multiple underlying models including GPT-4-level systems, file analysis, and a monthly API credit. For users doing serious daily research, Pro is worth the cost.

One practical advantage is honesty about sources. Every response cites where the information came from, making it easier to spot when a poor-quality source is being used or when sources disagree. This is more transparent than AI assistants that produce confident responses without references. However, Perplexity is not infallible: it can misread sources, get facts wrong, or select unreliable sources. The citations make these errors easier to catch.

The interface is clean and fast. Users can ask follow-up questions in a thread, share research threads, and on Pro, choose which model handles each query. Mobile apps make it easy to use as a daily research companion.

Where Perplexity is less useful is for generating, writing, or creating content. For those tasks, ChatGPT or Claude perform better. Perplexity is a research and information tool, not a creative one.