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Perplexity for business — AI-powered search

Perplexity for business: AI search and research with cited sources, document analysis, and real-time competitive intelligence.

Smart search that cites its sources

Google answers simple questions. Generative LLMs answer fluently but without verifiable sources and with a risk of hallucination. Perplexity fills a different space: it combines real-time search with generative synthesis, and cites the source of every claim. The result is an answer you can verify, not just consume.

For business settings where accuracy and traceability matter — market analysis, regulatory monitoring, technical research — that changes how useful the tool is.

Business use cases

Competitive intelligence

Keeping tabs on competitors is an ongoing job that eats hours of manual searching, news reading, and source cross-checking. With Perplexity, you can ask direct questions — “What have the leading players in refrigerated logistics announced in the last three months?” — and get synthesized answers with the specific source for each data point.

Market research

Before launching a product or entering a new market, teams need to understand market size, key players, applicable regulation, and emerging trends. Perplexity speeds up this exploratory research phase, so your team goes into interviews and quantitative analysis with a solid knowledge base already in place.

Regulatory monitoring

For companies in regulated sectors — food, manufacturing, financial services — keeping up with regulatory change is critical. Perplexity handles direct questions about the current status of regulations, EU directives in the pipeline, or recent interpretation criteria, with direct citations to the official texts.

Technical research

Engineering and R&D teams use Perplexity to explore the state of the art in specific technologies, compare implementation options, or understand the known limits of an approach. Its ability to cite papers and technical documentation makes it more useful than generic LLMs for this kind of query.

Perplexity Enterprise: privacy and control

The Enterprise version adds features that are critical for corporate use: queries aren’t used to train models, internal documents uploaded for analysis are processed with privacy guarantees, and user and permission management is centralized.

Document analysis lets you upload PDFs, reports, or presentations and ask them direct questions, with the same cited-answer approach. That makes it useful for analyzing contracts, audit reports, purchased market studies, or lengthy technical documentation.

Fitting it into your workflow

Perplexity works best as a tool for exploration and research — not as a replacement for specialized databases or internal knowledge management systems. Paired with tools like NotebookLM (to analyze your own documents) or internal RAG systems (to query your company’s knowledge base), it makes up the most common knowledge management stack.

AIRES helps teams decide when to use each tool and build Perplexity into their research and analysis workflows, cutting the time it takes without compromising the quality of the result.


Frequently asked questions

How is Perplexity different from just searching on Google?

Google returns a list of links; Perplexity synthesizes information from multiple sources into a coherent answer and cites where each data point came from. For complex questions that require cross-checking several sources, Perplexity saves you the time of opening, reading, and synthesizing each result by hand.

Can Perplexity replace a market intelligence analyst?

No. Perplexity speeds up gathering public information, but strategic interpretation, validation with primary sources, and recommendations still require human judgment. It makes the analyst more efficient — it doesn’t replace them.

Is it available in languages other than English?

Yes. Perplexity understands and answers in Spanish, French, Italian, German, and other major European languages with high quality. For research on national markets or regulations, answers in the local language backed by local-language sources are especially useful for teams that don’t normally work in English.

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