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    Proalpha AI

    Why Does Agent-Based AI Need Business and Process Context?

    Many companies today use AI for individual tasks. In practice, this often results in pilot projects, assistant solutions, and siloed solutions with limited added value.
    True business value is only realized when AI understands the business context and takes relevant data, process logic, and business rules into account. That’s why Proalpha AI combines data, processes, business knowledge, and governance into an integrated layered architecture for industrial SMEs.
    Deeply integrated into your ERP processes, AI agents understand interrelationships, access a shared knowledge base, and collaborate across business units. This transforms isolated AI into an intelligent, process-oriented system that identifies risks, creates transparency, and supports better decision-making. Answers become recommendations. Applications become collaboration. In this way, Proalpha AI helps employees assess impacts and derive appropriate courses of action along the entire value chain.

    Your Benefits with Proalpha AI Agents
    IL-Digital-Digital Transformation

    Business Context Instead of Isolated Solutions

    Generic AI answers questions. Proalpha AI understands the business context, connects knowledge, and supports decision-making directly within the operational process.

    IL-Data-Visualize-Visualize-Data

    From Insights to Actions

    Don't just get answers – derive concrete actions and intelligently support processes.

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    Collaboration Along the Value Chain

    AI agents support employees in their day-to-day work, collaborate across departments, and guide decision-making throughout the entire value chain.

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    Trust Through Governance and Clear Roles

    AI decisions remain embedded within governance structures, roles, and corporate policies. They are traceable, controllable, and compliant with regulations at all times.

    Agentic AI in Your Business Units

    Over 100 business questions. Over 70 AI agents. One goal: better decisions.

    From production planning to procurement to customer service: AI agents operate directly within the business context, create transparency, provide quick answers to operational questions, and support employees in making informed decisions in their day-to-day work.

    Agentic AI


    > 100 Business Questions
    answered in a concrete and role-specific manner


    > 70 Agents
    for all ERP processes

    Production

    Examples:

    • Which orders will be completed late this week?
    • Which machines are overloaded today?
    • Where are conflicts arising?
    AI in Manufacturing

    Procurement

    Examples:

    • Which orders are delayed?
    • Which suppliers are the best alternative for Material X?
    • How much would Part X cost if we manufactured it ourselves?
    AI in Procurement

    Sales

    Examples:

    • Which orders are currently at risk of not being delivered?
    • Which customers should I call first today?
    • Which quotes have been open for a long time?
    AI in Sales

    Finance

    Examples:

    • Which cost centers are deviating the most from the plan?
    • What financial risks do I need to address this week?
    AI in Finance

    Materials Management

    Examples:

    • Which materials will be in short supply over the next 5 days?
    • Which safety stock levels are too high or too low?
    • Which parts haven’t we used in the last 12 months?
    AI in Materials Management

    Quality Management

    Examples:

    • Which parts or suppliers have the highest complaint rate?
    • What causes are recorded for error type X? How often have they occurred in the last 90 days?
    AI in Quality Management

    Service

    Examples:

    • Which service cases are open and overdue?
    • Are there any known issues with this machine model?
    • What spare parts do I need for the job at Customer X tomorrow?
    AI in Customer Service

    Working More Productively with AI Agents in Small and Medium-Sized Businesses – Four Typical Ways to Boost Efficiency

    Every day, employees spend time searching for, analyzing, coordinating, and preparing information. Proalpha AI takes over these tasks directly within the workflow, provides the relevant context, and helps you act faster.
    Corporate knowledge, processes, and best practices become immediately available and support daily workflows.
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    Find information faster

    Less time spent searching thanks to direct access to relevant information, documents, and company knowledge.

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    Speed Up Decision-Making

    Risks, priorities, and recommendations for action become automatically apparent.

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    Automate Routine Tasks

    Reports, analyses, and recurring process steps are intelligently prepared or executed.

    IL-KI-Artificial Intelligence-AI

    Manage Processes More Efficiently

    AI agents detect anomalies early on, assess their impact, and help determine the next steps.

    Our Approach to Agentic AI – Five Steps to Better Decisions

    Proalpha AI follows a clear principle: identify risks early, create transparency, and determine the appropriate actions. In this AI agent workflow, the agents support employees – from the initial indication of a problem to a concrete recommendation – in assessing complex situations more quickly and setting the right priorities.
    pA-Number-1

    Identifying Risks Early On

    Agentic AI detects critical deviations, bottlenecks, and potential conflicts of interest early on in the ongoing process. This allows employees to take corrective action before warning signs turn into actual delays, cost overruns, or quality issues.

    pA-Number-2

    Promote transparency

    Agentic AI aggregates relevant data, trends, and dependencies from various areas of the business and presents them in a clear and understandable way. This creates a shared view of the situation, enabling teams to prioritize tasks more quickly and make more informed decisions.

    pA-Digit-3

    Optimizing Planning & Processes

    Agentic AI analyzes planning statuses, capacities, and process steps within a business context and identifies specific opportunities for optimization. This allows processes to be managed more efficiently, resources to be allocated more effectively, and decisions to be based more closely on real business data.

    pA-Number-4

    Understanding Connections

    Agentic AI identifies patterns, anomalies, causes, and interactions across individual processes, systems, and areas. This makes it clear why a situation arises, what effects it may have, and where the most effective levers for improvement lie.

    pA-Number-5

    Identify Priorities & Actions

    Agentic AI evaluates action options based on urgency, impact, and business value, and suggests the next logical steps. This helps employees know what to focus on first and which actions will contribute most to stability, efficiency, and better results.

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    Proalpha AI Platform: The Foundation for Trustworthy and Scalable AI

    Agentic AI requires more than just powerful models. It needs a platform that connects data, processes, systems, and governance. The Proalpha AI Platform provides exactly this foundation. It enables AI to understand business context and process logic, access relevant information, and provide cross-functional support.

    With integrated governance, compliance, and role-based access and control mechanisms, all activities remain transparent and manageable. This enables companies to deploy AI securely, scale it in a controlled manner, and chart a path from individual AI applications to intelligently orchestrated business processes.

    About the Proalpha AI Platform
    Pa-WP-industrial-ai-for-smes-1920x1080

    Whitepaper: Industrial AI in Mid-Sized Companies

    How can small and medium-sized enterprises not only test AI but also use it effectively over the long term? This whitepaper highlights the challenges that arise when scaling up, explains why integrated data and processes are crucial, and shows you how to get started with industrial AI.

    FAQ – Frequently Asked Questions About Proalpha AI and Agentic AI

    • With Proalpha AI, AI agents operate directly within the context of the business and its processes. They understand interrelationships, access a shared knowledge base, and support employees across business units. While isolated AI applications support individual tasks, Proalpha AI integrates data, processes, organizational knowledge, and governance into a unified, process-oriented system.

    • The Proalpha AI Platform connects data, processes, systems, and governance. The AI agents are deeply integrated into ERP processes and access a shared knowledge base. This enables them to take relevant information and process logic into account within the business context.

    • The AI agents draw on a shared knowledge base and take into account data, developments, and interdependencies from various areas of the company. This creates a shared situational overview that helps employees coordinate, prioritize, and make decisions throughout the value chain.

    • Proalpha AI supports production, purchasing, sales, finance, materials management, quality management, and service. For example, the AI agents help with questions regarding delayed orders, customer orders at risk of missing delivery deadlines, cost center budget variances, critical materials, complaint rates, and open and overdue service cases.

    • Proalpha AI intelligently prepares or executes reports, analyses, and recurring process steps. The AI agents detect deviations, assess their impact, and suggest next steps. In doing so, AI decisions remain embedded within governance frameworks, roles, and corporate policies. This text does not specify which individual process steps are prepared or executed.

    • The Proalpha AI Platform features built-in governance, compliance, and role-based access and control mechanisms. AI decisions remain embedded within corporate policies; activities remain transparent and manageable. The specific technical implementation of these mechanisms is not described in detail in this text.

    • For Proalpha AI to be effective, data, processes, and governance must work together. The AI Check provides an initial assessment of where the company stands today and what potential exists for intelligent automation, better decision-making, and end-to-end orchestration. Specific minimum technical requirements are not listed in this text.