Training course · Perplexity · Automotive

Perplexity for the Automotive Industry

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

“Perplexity for the Automotive Industry” is designed for roles such as Engineering and requirements management staff, Purchasing and supplier management at OEMs and suppliers and Quality management and complaint handling and shows step by step how to use Perplexity productively, safely and transparently in Automotive – from the fundamentals to advanced workflows.

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Quality is a key focus: you learn to assess sources, cross-check claims and recognise typical failure patterns such as outdated or misattributed information.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.

The automotive industry is under immense pressure to change: electrification, software-defined vehicles, new competitors and demanding regulation are transforming manufacturers, suppliers and dealerships alike. Generative AI supports almost every stage of the value chain – from requirements management in engineering, through supplier communication and complaint handling in purchasing and quality, to sales and aftersales at the dealership. AI assistants help unlock specifications, standards and test reports, structure 8D reports or answer customer enquiries. AI agents connect data from different systems. What matters is protecting engineering know-how, meeting quality and safety standards and having clear approval processes.

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?

  • Engineering and requirements management staff
  • Purchasing and supplier management at OEMs and suppliers
  • Quality management and complaint handling
  • Sales, service and aftersales at dealerships
  • Production and logistics planning

Typical challenges we address

  • Extensive specifications, standards and requirement documents
  • Heavy documentation workload in quality management and complaints
  • Complex supply chains requiring constant coordination
  • Strict protection of engineering data and intellectual property

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.
  • Analyse technical documents such as specifications and standards with AI in a structured way.
  • Accelerate quality, complaint and supplier processes with AI support.
  • Use AI while upholding confidentiality, quality standards and approval processes.

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: Automotive
  • Analysing specifications
  • Complaints and 8D reports
  • Supplier communication
  • Unlocking standards and processes
  • Sales and aftersales
  • Training and technical documentation
Module 7 Data protection, quality & transfer to daily work
  • Engineering data, design documents and customer specifications are subject to strict confidentiality agreements and industry information security requirements such as TISAX, and may only be processed in approved AI environments. Customer data at dealerships falls under the GDPR, and safety-relevant content always requires expert sign-off.
  • 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

Analysing specifications

AI extracts requirements from lengthy customer specifications, compares them with the supplier's technical response, flags contradictions and ambiguities and drafts clarification questions for customers or development partners.

Complaints and 8D reports

Complaint descriptions are structured, potential causes gathered using methods such as Ishikawa and 8D reports written in clear language – root cause analysis remains the expert team's job.

Supplier communication

Requests, formal notices, escalations and audit reports are written precisely and in several languages, supplier ratings are commented on and meeting preparation is produced. Agreements are recorded for follow-up.

Unlocking standards and processes

Internal process descriptions, work instructions and quality requirements are made searchable, so staff receive answers with a reference to the governing document. New staff find applicable rules much faster.

Sales and aftersales

At the dealership, AI drafts offers, vehicle descriptions, replies to customer enquiries and service reminders and helps service advisers explain repairs clearly. Customer requests are captured for follow-up in the CRM.

Training and technical documentation

Training materials for assembly, service or new vehicle technologies are created from technical documents, simplified for the audience and translated into other languages. Quiz questions per chapter are included.

Prerequisites

Experience with online research in a professional context; no prior AI knowledge is required. Professional experience at a vehicle manufacturer, supplier or dealership; 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

Engineering data, design documents and customer specifications are subject to strict confidentiality agreements and industry information security requirements such as TISAX, and may only be processed in approved AI environments. Customer data at dealerships falls under the GDPR, and safety-relevant content always requires expert sign-off.

Suggested dates

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

  • Mon, 23 November 2026 Online Request
  • Wed, 9 December 2026 Stuttgart Request
  • Thu, 14 January 2027 Online Request
  • Fri, 29 January 2027 Berlin Request
  • Fri, 5 February 2027 Online Request
  • Fri, 19 February 2027 Munich 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 specifications be uploaded to AI tools?

Only into environments approved by your information security team that meet your customers' requirements. Many OEMs regulate this contractually. The course shows how to work with approved enterprise solutions, clean documents beforehand and which content never belongs in external services.

Can AI carry out a root cause analysis?

AI helps gather potential causes systematically, structure methods such as 5 Whys or Ishikawa and write reports. The actual analysis with measurements, tests and process knowledge remains the expert team's task. AI speeds up the path there and improves documentation quality.

How much does “Perplexity for the Automotive Industry” 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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