Perplexity Spaces

What is Perplexity Spaces?

Perplexity Spaces is a collaborative research and knowledge management feature within Perplexity AI, the AI-powered answer engine. Spaces allows users to create dedicated, customizable knowledge bases where they can upload files, save sources, set custom instructions, and collaborate with team members on research projects. Unlike standard Perplexity searches which draw from the open web, Spaces lets you constrain the AI's knowledge to specific documents and sources you provide, making it a powerful tool for team research, competitive analysis, academic literature reviews, and internal knowledge management.

Perplexity AI itself was founded in 2022 by Aravind Srinivas, Denis Yarats, Johnny Ho, and Andy Konwinski — all former researchers from OpenAI, Meta AI, and Quora. The platform has grown rapidly by offering a conversational search experience that cites sources, making it a popular alternative to traditional search engines and ChatGPT. Spaces extends this capability by adding persistence, customization, and collaboration — three features that standard AI chat interfaces lack.

What differentiates Perplexity Spaces from similar features in ChatGPT (Custom GPTs) or Google's NotebookLM is its focus on research workflows. Spaces is designed around the idea of collecting, organizing, and querying information — not just chatting with an AI. Each Space maintains its own context, source library, and instruction set, allowing teams to build living research repositories that grow over time.

Key Features

Custom Knowledge Bases

Each Space can have its own knowledge base built from uploaded files (PDFs, Word documents, text files, images with text) and saved web sources. When you ask a question within a Space, Perplexity prioritizes these sources over general web search. This means you can create a Space for a specific project — say, a competitor analysis — upload all relevant reports and articles, and get answers grounded entirely in those materials.

Custom Instructions

Space creators can set custom instructions that define how the AI should behave within that Space. For example, you can instruct it to "always respond in bullet points with citations from the uploaded documents" or "focus on technical specifications rather than marketing language." These instructions persist across all queries in the Space, ensuring consistent output formatting and tone.

Collaborative Research

Spaces can be shared with team members who can contribute sources, ask questions, and view the research history. Each member's queries and the AI's responses are visible to the entire team, creating a shared research log. This eliminates the need for separate documents, email threads, or Slack messages to coordinate research efforts — everything happens within the Space.

Source Management and Citation

Every response in a Space includes numbered citations linking back to the specific sources used. You can add, remove, or reorganize sources at any time. The source library shows all documents and links associated with the Space, making it easy to audit where information came from. This is particularly valuable for academic research, legal analysis, and any domain where source attribution matters.

Collection Organization

Users can create multiple Spaces for different projects, topics, or teams. Each Space maintains its own separate context and source library — queries in one Space do not affect another. This allows researchers to compartmentalize their work without cross-contamination of context between unrelated projects.

Multi-Model Support

Perplexity Spaces works across Perplexity's available AI models, including GPT-4, Claude, and Perplexity's own models. Users can select which model powers their Space, allowing them to choose between different reasoning styles, speed, and cost profiles depending on the task at hand.

Pro Search and Deep Research

Spaces supports Perplexity's Pro Search feature, which performs deeper, multi-step reasoning on complex queries. For research-intensive tasks, the Deep Research mode can spend more time analyzing sources and generating comprehensive answers, making Spaces suitable for serious research work rather than just quick lookups.

Who Should Use It

Research teams in academic, legal, or market research settings who need to collaborate on literature reviews, competitive analysis, or regulatory research. Spaces provides a shared, auditable research environment with proper source attribution.

Product and strategy teams who need to maintain ongoing competitive intelligence. A Space can serve as a living repository of competitor news, product updates, and market analysis that the entire team can query.

Students and academics working on literature reviews or thesis research. Spaces allows you to upload papers, save web sources, and ask questions grounded in your specific source set — reducing the risk of hallucinated citations.

Consultants and analysts who need to produce research-backed reports for clients. Spaces can be organized per client or per project, with all relevant documents and analysis in one place.

Content creators and journalists who need to research topics thoroughly before writing. Spaces provides a structured way to collect sources, take AI-assisted notes, and ensure factual accuracy through citation verification.

Pricing

Perplexity Spaces is available on Perplexity's paid plans:

• Perplexity Pro ($20/month): Includes unlimited Pro searches, file uploads, and Spaces creation. This is the entry point for using Spaces with full features.
• Perplexity Pro ($200/year annual): Discounted annual billing option for the Pro plan.
• Enterprise/Team Plans: Custom pricing for organizations that need admin controls, SSO, and team management features. Includes dedicated support and usage analytics.

The free tier of Perplexity offers basic search with limited Pro queries per day but does not include Spaces functionality. A Pro subscription is required to create and collaborate in Spaces.

Pros & Cons

Pros

• Source-grounded answers. Unlike general AI chatbots that may hallucinate, Spaces prioritizes your uploaded documents and saved sources, producing more reliable and verifiable responses.
• Persistent context. Each Space maintains its own knowledge base and conversation history. You can return to a Space weeks later and pick up where you left off without losing context.
• Team collaboration. Shared Spaces with visible research history reduce duplication of effort and keep everyone on the same page.
• Custom instructions. The ability to set persistent behavior rules makes Spaces adaptable to different use cases — from academic research to competitive analysis.
• Clean citation system. Numbered citations with direct links to sources make it easy to verify claims and dig deeper into specific documents.

Cons

• Pro subscription required. Spaces is not available on the free tier, which limits access for casual users or students on a tight budget.
• Limited file format support. While PDFs and common document formats are supported, more specialized formats (spreadsheets, databases, code repositories) are not natively handled.
• No offline access. Spaces are cloud-only. You cannot access your knowledge bases without an internet connection.
• Source library size limits. There are practical limits on how many files and sources a single Space can hold, which may be restrictive for large-scale research projects.
• Competition from alternatives. ChatGPT's Custom GPTs, Google's NotebookLM, and Microsoft Copilot offer similar features, sometimes with deeper integration into their respective ecosystems.

Alternatives

ChatGPT Custom GPTs (ChatGPT Plus, $20/month)

OpenAI's Custom GPTs allow users to create tailored versions of ChatGPT with custom instructions, uploaded knowledge files, and specific capabilities (web browsing, DALL-E, code interpreter). Custom GPTs have a broader capability set than Perplexity Spaces — they can generate images, run code, and browse the web — but their research focus is less sharp. Perplexity Spaces is superior for source-grounded research because Perplexity was built as a search engine first, whereas ChatGPT was built as a general-purpose chatbot. Browse more AI assistant tools on PureAINav.

Google NotebookLM (Free)

NotebookLM is Google's AI-powered research assistant that lets you upload documents and ask questions grounded in those sources. It is completely free and offers excellent source-grounded responses with automatic citation. NotebookLM also generates podcast-style audio summaries of your sources. However, it lacks the team collaboration features of Perplexity Spaces — NotebookLM is currently a single-user tool. It is the better choice for individual researchers who want a free, powerful research assistant.

Microsoft Copilot with Enterprise Data Protection (Free/Paid)

Microsoft Copilot (formerly Bing Chat) offers grounded search with citations and can be extended with Microsoft Graph for enterprise data access. For organizations already in the Microsoft ecosystem, Copilot provides deeper integration with SharePoint, Teams, and Office documents. However, its Spaces-like functionality is less mature than Perplexity's, and the citation quality varies depending on the query complexity.

Ready to explore more AI-powered research and assistant tools? Visit the AI Assistants category on PureAINav for a curated selection of the best AI tools for productivity and research.