Perplexity Enterprise for Finance

Discover how Perplexity Enterprise delivers trusted, auditable answers by combining custom web indexing, tailored research queries, and deep data analysis—all in one platform. Finance teams use Perplexity to get market updates, customize answer engines, access SEC filings, and create live data visualizations.

Using Perplexity to conduct Market Overviews
I want to see how many cities have allowed robotaxis to operate. Then I want to see how many cities are evaluating whether robotaxis should operate. And finally, I want to see cities that have outright banned the operation of robotaxis.

Perplexity: Trust & Accuracy
What makes Perplexity different from other chatbots or AI companies is we've indexed the web ourselves. We use our custom index to give you the best answers. Like with the 10 blue links, we find those and then feed them to the best AI model for your question. We're model agnostic. We also differentiate by giving you beautifully formatted answers that are easy to audit. We really want to strive for trust and accuracy, so you can check sources for every point in an answer, seeing exactly where the information comes from.

Scheduling Market Updates
Seeing that robotaxis are active in cities like Phoenix, San Francisco, and Las Vegas, I want to get updates on this. I can schedule a task to run every week on Tuesday mornings at 9AM to send me an update on the robotaxi market and what's changed. I want this delivered on a weekly basis, so I add it as a recurring job and set it up as a deep research query.

Custom Answer Engines
There's something we call "spaces," where you can build custom answer engines. There are spaces for many use cases, like creating company profiles. For example, if I have a specific style for a Waymo company profile, I can set a master prompt so every time I prompt for a profile, it returns in a consistent format: overview, products and services, leaders, financials, recent news, and so on. Spaces can be copied and tailored to your needs.

Waymo, Tesla, Uber Plans
I've uploaded a lot of information into a space and can now ask for a detailed perspective on how Waymo, Tesla, and Uber plan to make money in the robotaxi space. I can toggle on deep research and restrict sources to their own reports, like SEC filings. This way, I get management's own perspective and can pull from different relevant documents.

Robotaxi Market Analysis
After gathering these insights, I want to understand the total addressable market for robotaxis. I take the total miles driven in the US, assume 10% penetration, the revenue per mile Uber charges, multiply by a 20% market share, then by a 20% EBITDA margin, and apply a 15x EV to EBITDA multiple. Running this in the platform, I get an enterprise value and can analyze and compare it with other sources like McKinsey and Zion Market.

Adding Custom Data
You can add custom data. For example, I want to dive deeper into Uber using some credit card company data I've found, which details Uber vs. Lyft. I dump this data in, and the platform generates visualizations and analysis using Python, giving me clear, objective takeaways about trends in market share and user engagement.

Uber vs. Lyft: Market Share
Seeing the market share dynamic, Lyft appears to be doing really well and could be a significant winner in the robotaxi market. There are different patterns for frequent and infrequent users, as well as differences in monthly card spend.

Demo Conclusion
Overall, by bringing in a lot of data, I get full reports and visualizations and can iteratively ask follow-up questions. Hope you've enjoyed this demo. Reach out if you'd like to talk more.