Training course · Perplexity · Founders & Startups

Perplexity for Founders and Startups

AI-powered research with Perplexity: cited answers, source control, Spaces, Deep Research and systematic fact-checking.

Duration
1 day (7 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

This course connects Perplexity with the everyday processes of Founders & Startups. Participants work on realistic scenarios and leave with prompts, workflows and checklists they can use straight away.

Perplexity combines language models with live web search and delivers answers backed by numbered citations. That makes it particularly suited to work where currency and traceability matter: market and competitor monitoring, research into regulation and standards, supplier and partner due diligence, or preparing decision papers. In this practical day you learn to phrase research questions precisely, steer the choice of sources deliberately and use follow-up questions to turn an initial answer into a robust research result.

You work with Spaces, where you group research on a topic, add your own files and set instructions for the team. With Deep Research you produce extensive reports that evaluate many sources and bring them together in a structured way. Quality is a key focus: you learn to assess sources, cross-check claims and recognise typical failure patterns such as outdated or misattributed information. We also address data protection and licensing questions for business use. You leave with a reusable research process tailored to your own function.

Founders have to juggle many roles with a small team and limited budget: product, sales, marketing, finance, hiring and investor relations. Generative AI acts like an extra team member. It helps with market research and competitor analysis, drafts pitch decks and investor updates, writes landing pages and sales emails, structures customer interviews and supports the financial model. With vibe coding, prototypes, clickable mock-ups and internal tools come together in hours rather than weeks, so hypotheses can be tested in the market much sooner. AI agents automate lead research, onboarding emails or support replies. The key is to combine speed with critical review and to get the legal basics right from day one.

The course is delivered live – either online in a virtual classroom or on-site in our training rooms in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run it exclusively for your team.

Who is this course for?

  • Early-stage founders
  • Founding teams in incubators and accelerators
  • Early employees at startups
  • Corporate venturing and intrapreneurship teams
  • Solo entrepreneurs with product ideas

Typical challenges we address

  • Little time and few resources for many parallel tasks
  • Hypotheses need to be validated quickly and cheaply
  • Heavy effort for pitching, investor relations and grant applications
  • No in-house experts for legal, finance and development in the early stage

What you will be able to do

  • You phrase precise research questions and steer the choice of sources deliberately.
  • You assess sources by origin, currency and reliability and trace claims back to the original.
  • You organise research in Spaces and combine web sources with your own documents.
  • You use Deep Research to produce structured reports and decision support.
  • Validate business ideas faster with AI through research, interviews and prototypes.
  • Produce pitch decks, investor updates and sales materials efficiently with AI.
  • Build simple prototypes and internal tools through vibe coding and understand their limits.

Course outline

Module 1 Foundations of AI-powered research
  • How it works: language model, live web search and citations
  • How it differs from a classic search engine and a general chat assistant
  • Framing research questions precisely: time frame, region, source type
  • Follow-ups and drilling down instead of one-off queries
Module 2 Steering and assessing sources
  • Narrowing sources: web, academic literature, your own files
  • Targeting primary sources, official websites and specialist publications
  • Assessing source quality: origin, currency, vested interests
  • Tracing quotes and figures back to the original source
Module 3 Spaces and teamwork
  • Setting up Spaces for topics, projects or client requests
  • Uploading your own documents and combining them with web sources
  • Storing instructions for consistent output formats
  • Sharing research and turning it into pages or reports
Module 4 Deep Research and structured reports
  • Tackling broad questions with Deep Research
  • Producing market overviews, competitor comparisons and topic briefs
  • Turning results into tables, side-by-side comparisons and executive summaries
  • Recognising the limits of in-depth research and refining results
Module 5 Fact-checking, data protection and workflow
  • Systematic fact-checking: counter-research and spotting contradictions
  • Typical failure patterns: outdated, misattributed or fabricated details
  • Data protection, enterprise licences and handling confidential queries
  • A reusable research process and source documentation
Module 6 Practice lab: Founders & Startups
  • Market and competitor analysis
  • Analysing customer interviews
  • Pitch decks and investor updates
  • Prototypes via vibe coding
  • Sales and marketing
  • Grants and business plans
Module 7 Data protection, quality & transfer to daily work
  • Startups must comply with the GDPR, imprint requirements and unfair competition law from the outset, for example for waitlists, newsletters and outreach. For AI-based products, the EU AI Act, copyright in generated content, code licences and the confidentiality of investor and customer data must be considered.
  • Ground rules for safe AI use in your team
  • Checking results: facts, sources, tests and the four-eyes principle
  • Personal action plan for the next 30 days
  • Open questions, outlook and resources for further learning

Practical scenarios from your field

Market and competitor analysis

AI structures market segments, target groups and competitors, derives positioning options and helps identify research sources – figures and facts are then backed up with reliable references.

Analysing customer interviews

Guides for problem interviews are created, notes are analysed for pain points, willingness to pay and quotes, and insights are condensed for the next iteration.

Pitch decks and investor updates

Storyline, slide copy and answers to typical investor questions are developed; regular updates for investors and advisers are generated from KPIs and milestones. Investors stay informed with little effort.

Prototypes via vibe coding

Landing pages, clickable prototypes and simple MVPs are built with AI coding tools to test demand and user behaviour before investing in professional development. Scaling up follows once demand is confirmed.

Sales and marketing

Ideal customer profiles, outreach sequences, website copy and social posts are written for the target audience and prepared in variants for A/B testing. Test results feed straight into the next iteration.

Grants and business plans

AI helps make sense of funding programmes, structure applications and business plans and explain financial assumptions clearly; the figures themselves are checked by an expert.

Prerequisites

Experience with online research in a professional context; no prior AI knowledge is required. A startup idea or a role in a young company; no programming skills required.

Technical requirements

A laptop with an up-to-date browser and a Perplexity account; we recommend Pro or Enterprise access to use Spaces with files and Deep Research in full.

Data protection & compliance

Startups must comply with the GDPR, imprint requirements and unfair competition law from the outset, for example for waitlists, newsletters and outreach. For AI-based products, the EU AI Act, copyright in generated content, code licences and the confidentiality of investor and customer data must be considered.

Suggested dates

All dates are suggestions – your preferred date is always possible.

  • Fri, 27 November 2026 Online Request
  • Thu, 10 December 2026 Berlin Request
  • Wed, 16 December 2026 Online Request
  • Fri, 8 January 2027 Online Request
  • Thu, 14 January 2027 Stuttgart Request
  • Mon, 18 January 2027 Online Request

Frequently asked questions

How does Perplexity differ from ChatGPT or a search engine?

A search engine returns a list of links, and a general chat assistant often answers from its training data. Perplexity searches the web at the moment you ask, summarises what it finds and backs each statement with citations. That makes it particularly well suited to current, verifiable research – although you still need to assess the sources yourself.

Can I rely on Perplexity's citations?

Citations make verification much easier, but they do not replace it. Occasionally a statement is attributed to a source that does not say quite that, or an outdated page is used. In the course you learn a lean fact-checking routine that lets you quickly verify critical statements against the original source.

Is Perplexity suitable for confidential research within a company?

Enterprise plans offer additional commitments on data use and administration. Even so, you should not put trade secrets or personal data into queries unless your internal policy explicitly allows it. We discuss how to phrase queries so that sensitive details stay protected while the research remains useful.

Can I build an MVP with AI without knowing how to code?

For landing pages, clickable prototypes and simple web apps, yes – often enough to test demand. For a scalable, secure product handling user data and payments, however, you need development expertise. The course shows where that line lies and how to hand prototypes over cleanly to developers.

Can investors tell a pitch deck was written by AI?

Generic copy stands out. What matters is that the storyline, numbers and insights come from your own work. AI helps you structure, sharpen and prepare for tough questions. In the course we practise making your story more compelling with AI without sounding interchangeable.

How much does “Perplexity for Founders and Startups” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 1 training day(s) with a live trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. Our suggested dates are just a guide. In the request form you can always describe your preferred date or period in free text – we check availability and confirm within one working day.

Is the course online or on-site?

Both are possible: live online in a virtual classroom or on-site in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart or Kaiserslautern. We can also run the course exclusively for your team.

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