AI for System Analysts
Level
IntermediateDuration
8h / 1 dayDate
Individually arrangedPrice
Individually arrangedAI for System Analysts
Learn how to use local AI models to automate the analysis of documentation and the management of system requirements. Participants will learn to generate user stories, diagrams, acceptance criteria, and automatically create tickets in Jira. The training shows how to monitor requirement consistency and identify risks using workflows in n8n. This practical AI approach for IT systems allows increasing the efficiency of analysts’ work and improving documentation processes.
Participant Requirements
- Basic knowledge of requirements analysis and system documentation
- Basic knowledge of tools such as Jira / Confluence
- Basic understanding of development processes and Agile
- Ability to run a local AI model (Ollama / LM Studio)
What You Will Learn
- Create a local “system analyst copilot” for working with documentation
- Automate the generation of user stories, acceptance criteria, and diagrams
- Build an agent analyzing requirement consistency, detecting risks, and generating reports ready for Confluence
Who is this training for?
System analysts-
Specialists in business processes and requirements
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Product Owners collaborating with dev and QA teams
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People responsible for automating documentation and requirements management
Training Program
Scope of topics:
- Local AI for documentation analysis (without sending data externally)
- Generating user stories, diagrams, and acceptance criteria
- Automatically creating a base for issues in Jira
- Monitoring requirement consistency and identifying risks
- Automatic change reports
Theoretical knowledge:
- How a local LLM (Ollama / LM Studio) works and why it does not need to use the cloud
- Brief introduction to RAG (local knowledge base from documents → better answers)
- When to trust AI and when human validation is required (quality control of requirements)
- Basics of orchestration of steps in n8n and agents
Practical tasks:
- Launching a local analytical assistant:
- Input system documentation
- Building a basic RAG system with n8n
- Working with the knowledge base
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Automatic generation of documentation:
- User stories, roles/actors, acceptance criteria, diagram sketches (Mermaid / PlantUML)
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Building a workflow to generate Jira issues content:
- Splitting into dev tasks, priorities, DoR, acceptance
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Building an analytical agent:
- Checks new requirements for conflicts/gaps
- Creates risk and change reports in a format ready for Confluence
Tools (used during the workshop):
- Ollama / LM Studio (local language models)
- n8n (automation: ticket generation, reports)
- Jira / Confluence (as target output formats)
- Mermaid / PlantUML (text-based diagram generation)
Outcomes:
- A working local “system analyst copilot” that understands company documentation
- Ready n8n pipeline template for semi-automatic creation of Jira tickets with DoR and acceptance criteria
- Diagram generator and question lists for the Product Owner
- Requirement compliance and risk detection agent that can be integrated into existing analysis processes
