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Claude AI in the analysis of documents, reports and business documentation

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Training process

Training needs analysis

If you have specific requirements regarding the training programme, we will carry out a training needs analysis for you. This will guide us on which aspects of the programme should receive greater emphasis, so that the training programme meets your specific needs.

What will you gain?

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Efficient work with large documents - You will learn how to analyze long PDFs, Word files, spreadsheets, and presentations without manually digging through them, so you can reach the most important findings much faster.

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Better use of scans and OCR - You will learn how to handle scanned documents, assess text recognition quality, and spot OCR errors, so your conclusions are not based on incomplete or distorted source material.

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Sharper summaries in less time - You will create executive summaries, management notes, and decision-ready reports tailored to the audience, making it easier to present the core message to leaders, clients, or teams.

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Business report and process analysis - You will learn how to extract trends, risks, and dependencies from financial, sales, operational, and process documents, helping you prepare stronger business recommendations.

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Faster contract and risk review - You will practice identifying liability clauses, penalties, deadlines, and risk provisions in contracts, so you can quickly flag sections that require review, escalation, or negotiation.

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Effective technical documentation analysis - You will work with specifications, API docs, business requirements, and user stories, so you can connect technical details with project goals and user needs more confidently.

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Combining insight from many sources - You will learn how to compare multiple documents at once, detect inconsistencies, build structured comparisons, and produce consolidated reports for offers, procedures, or standards.

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Your own templates and safe workflow - You will build reusable prompts, analysis templates, and validation rules, so you can work faster, reduce AI misinterpretations, and handle confidential document content more safely.

Training programme

1. Introduction to Claude AI in working with documents

  • what Claude is and how it differs from other AI models:
    • Claude as a tool for working with large documents,
    • capabilities for working with PDF, DOCX, XLSX files and presentations,
    • handling multi-page documents,
    • limitations and best practices,
  • organization of work with documents in Claude:
    • projects (Projects),
    • artifacts (Artifacts),
    • building a knowledge repository,
    • context and analysis history management.

2. Importing and processing documents

  • loading documents into Claude:
    • PDFs,
    • Word documents,
    • PowerPoint presentations,
    • Excel spreadsheets,
    • technical documentation,
  • working with scanned documents:
    • OCR and text recognition,
    • document quality issues,
    • verification of reading correctness,
  • analysis of the document structure:
    • tables of contents,
    • sections and chapters,
    • tables,
    • charts,
    • diagrams and schematics.

3. Automatic document summarization

  • creating summaries:
    • Executive Summary
    • managerial summary
    • technical summary
    • summary for the management board
  • extraction of the most important information:
    • key conclusions,
    • risks,
    • recommendations,
    • actions to be taken,
  • Creating notes and reports:
    • meeting notes,
    • periodic reports,
    • project summaries,
    • decision documents.

4. Analysis of business documents

  • analysis of reports and statements:
    • financial reports,
    • sales reports,
    • operational reports,
    • ESG reports,
  • information retrieval:
    • searching for specific entries,
    • trend analysis,
    • identification of relationships,
    • creating summaries,
  • analysis of business processes:
    • process documentation,
    • procedures,
    • operating instructions,
    • organizational policies.

5. Analysis of contracts and legal documents

  • review of legal documents:
    • commercial contracts,
    • IT contracts,
    • NDAs,
    • regulations and procedures,
  • searching for key provisions:
    • liability of the parties,
    • contractual penalties,
    • performance deadlines,
    • risk clauses,
  • comparing documents:
    • analysis of differences between versions,
    • identification of changes,
    • creation of change reports,
    • verification of compliance.

6. Technical documentation analysis

  • IT and system documentation:
    • technical specifications,
    • API documentation,
    • systems documentation,
    • implementation instructions,
  • working with project documentation:
    • business requirements,
    • User Stories,
    • functional descriptions,
    • architecture documentation,
  • building a knowledge base:
    • creating internal documentation,
    • FAQ,
    • knowledge repository,
    • instructions for users.

7. Analysis of research and scientific documents

  • working with scientific publications:
    • analysis of articles,
    • searching for research methods,
    • identification of research results,
    • assessment of publication quality,
  • literature review:
    • comparing publications,
    • analysis of research trends,
    • creating literature reviews,
    • building expert knowledge bases.

8. Analysis of multiple documents simultaneously

  • Cross-document analysis:
    • combining information from multiple sources,
    • detecting inconsistencies,
    • compliance analysis,
    • creating aggregate reports,
  • Document benchmarking:
    • comparison of offers,
    • comparison of procedures,
    • competition analysis,
    • standards analysis,
  • knowledge synthesis:
    • creating aggregate reports,
    • building recommendations,
    • mapping dependencies,
    • creating information dashboards.

9. Advanced prompting techniques

  • designing effective prompts:
    • expert analysis,
    • legal analysis,
    • financial analysis,
    • technical analysis,
  • creating analysis templates:
    • report templates,
    • audit templates,
    • document assessment templates,
    • automation of repetitive analyses,
  • iterative work with the document:
    • deepening the analysis,
    • asking contextual questions,
    • validation of responses,
    • elimination of interpretative errors.

10. Security and good practices

  • data protection:
    • confidential data,
    • personal data,
    • business information,
    • internal documents,
  • quality control of analyses:
    • verification of AI responses,
    • identification of hallucinations,
    • validation of sources,
    • audit of results,
  • practical workshop:
    • analysis of participants' real documents,
    • creation of own analysis templates,
    • automation of daily documentation tasks,
    • preparation of individual workflows for working with Claude.

What are the prerequisites for participating in the training?

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Basic document handling - You should be comfortable working with PDFs, Word files, spreadsheets, and presentations, so during the training you can focus on analysis rather than basic file handling.

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Business context awareness - You should understand core terms used in reports, procedures, and business documentation, so you can interpret analysis results correctly and ask meaningful follow-up questions.

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Ability to frame clear questions - You should be able to describe a problem, analysis goal, or expected output clearly, because effective work with Claude depends on precise prompts and document-related instructions.

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Awareness of data sensitivity - You should understand which documents contain confidential, personal, or business-sensitive data, so you can use AI responsibly during exercises and in your later day-to-day work.