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    APRIXITY ACADEMY

    Process optimization: Understand, simplify, automate.

    Training, workshops and analyses for companies that want to use AI safely, make their data usable and improve processes with precision.

    View programs

    PROGRAMS

    Where would you like to start?

    You can start at any point.

    Illustrative sample · not a customer reference

    Internal use record: writing assistant in sales

    Records what the team uses the system for, where people review, and which learning goals remain open.

    Purpose
    Prepare drafts of property descriptions
    Human review
    Facts, discriminatory wording, and approval before publication
    Open learning task
    Recognise and remove confidential data before entry
    Documented evidence
    Example task with review criteria and team questions
    Retained output
    Internal documentation for continued instruction and review.
    Preparation
    Systems in use, roles, typical tasks, and known uncertainties.
    Boundary
    No certification, legal advice, compliance guarantee, or system implementation.

    Tailored to your operation.

    Content, examples and exercises reflect your existing stack, your real workflows and your team's experience.

    Before the session, three short questions clarify the systems you use, the team's experience and the workflow that should improve.

    AI literacy

    AI Literacy Training (Article 4 EU AI Act)

    Situation
    AI is already in use or planned, but the team lacks a shared operating standard.
    Content
    Context-specific work on the AI systems in use: roles and prior knowledge, purpose, affected groups, risks, safe use, limitations and human responsibility.
    Format
    In-house training for teams
    Retained artifact
    Internal record of systems, risks, learning objectives, content and participants
    Boundary
    Training and internal documentation; no system implementation, individual legal advice, certification or compliance guarantee.
    Enquire about AI literacy training

    Data & company knowledge

    Data Workshop

    Situation
    Relevant data and operational knowledge exist, but there is no shared view of sources, quality, gaps and ownership.
    Content
    Data quality and knowledge documentation as prerequisites for dependable AI use.
    Format
    facilitated workshop
    Retained artifact
    Data map and knowledge inventory
    Boundary
    Shared inventory and decision basis; no prototype or system implementation.
    Enquire about the Data Workshop

    Processes & automation

    Process Capture

    Situation
    There is no reliable view of the current process, making work, waiting, handoffs and information loss difficult to see.
    Content
    Make the work sequence visible, identify bottlenecks and establish decision criteria for prioritization.
    Format
    facilitated on-site workshop
    Retained artifact
    Process landscape, bottlenecks and prioritization matrix
    Boundary
    Visibility and prioritization; no implementation roadmap or system build.
    Enquire about Process Capture

    Bottleneck Analysis

    Situation
    A usable process map and target exist, but the binding constraint and sensible implementation order are unclear.
    Content
    Structured analysis of the constraint, its operational effects and the order of possible interventions.
    Format
    structured analysis
    Retained artifact
    Prioritized roadmap
    Boundary
    Prioritization and implementation order; no process capture or implementation.
    Enquire about Bottleneck Analysis

    A concrete case rather than a learning objective?

    The Academy enables teams. A concrete operational AI case that needs a decision belongs in AI consulting.

    Go to AI consulting Hannover

    The method in five thought movements

    Understand first, then simplify, then automate.

    Clarify the target and constraint. Remove ballast. Simplify the flow. Supply required context at the point of work. Prove it on a small scale.

    View the method

    Frequently asked questions

    Providers and deployers of AI systems must take measures to support the development of AI literacy among their staff and other persons dealing with the operation or use of AI systems on their behalf. Appropriate measures depend on prior knowledge, roles, systems used, purpose and risks. Article 4 mandates neither a specific individual competence level nor a certificate or uniform course format; training, guidance and other measures can be documented internally.

    Most processes are not complex but complicated: many steps, yet each one can be traced. A complicated process can be mapped, simplified and then automated with precision. The size of your company is no reason to stop — it is the reason to start by understanding.

    Questions about the appropriate offer?

    Write to us with the process or situation you want to clarify.

    hello@aprixity.run