Artificial Intelligence (AI) will be one of the major drivers in technology and business digitalization in the coming years. AI is a subfield of computer science that enables machines to mimic cognitive human behavior. As human behavior is quite complex, it is typically divided into several disciplines, e.g. robotics, planning, problem solving, language processing or machine learning.

Camelot leverages Artificial Intelligence to create value for clients by enabling data-driven decision-making within the client’s value chain.

AI along the value chain

Why AI?

Artificial Intelligence is already a part of the core business processes in many industries. Key benefits of AI implementation include a significant cost reduction, productivity and profit boost.

Many processes within a company’s value chain can be automated using AI technologies.


Simple tasks can be handed to machines, so staff can focus more on making strategic decisions based on the output and recommendations provided by the AI platform.

Any usage of AI helps to reduce costs and increase productivity. By optimizing business processes with Machine Learning (ML) technologies and introducing innovations, AI can boost long-lasting profitability


Productivity boost

Help clients to reap the full benefits of data initiatives from strategy to implementation. Identify business cases that fit their strategic needs, develop appropriate governance frameworks, and realize the implementation cost effectively.

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Profit boost

Develop differentiated strategies to maximize customer profitability by gaining visibility into a customer’s cost and profit data.


Cost reduction

Simulate alternative supply methods & combinations (including global sourcing and make vs. buy decisions). Reduction of cost per unit for different supply chain options.

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Interested to learn how your value chain can be enriched by AI?

AI along the value chain

The main goal of using Artificial Intelligence is to deliver value to the user by performing data-driven decision-making. AI can be applied across the entire value chain of an enterprise.

Sourcing & Network Collaboration
Supply Chain Operations & Manufacturing
Distribution & Logistics
Sales & Customer Centricity
Information Management & Digital Innovation

Supply Chain Management

  • Demand Planning improvements by automated pattern recognition
  • Forecast improvements to support strategic, tactical and operational decisions
  • Chatbot and cognitive services to improve user experience within ERP systems
  • Production planning accuracy improvement
  • Improved material requirements planning by linking stocking point and replenishment cycles to value constraints
Demand Planning Use Case


  • Reduced freight costs due to better ordering behavior for utilization of freight capacity
  • Smart Tendering (freight purchase): When to tender, what to tender, how to tender
  • Increase of freight rates due to stronger purchasing position
Logistics Use Case

Master Data Management

  • Data plausibility checks based on unstructured and transactional data
  • Predict data extensions and proactively maintain data
  • Clustering: For example, to define an optimal set of payment terms based on customer/supplier and transactional data
  • Chatbot to guide users and to explain data dependencies for improved usability of MDM tools
  • Automated data record linking/mapping and duplicate detection with no need for harmonization
MDG Chatbot Use Case
AI as Key Enabler for Business Digitalization

Use Cases

Camelot provides innovative use cases and solutions across the value chain.

Demand Planning

Demand Planning

The Camelot best practice demand planning process includes various use cases of artificial intelligence and data science throughout the planning cycle. Exemplary applications are convolutional neural networks for time-series pattern detection, neural networks to predict sporadic demand or neural networks for price sensitivity analysis.


MDM Chatbot

MDM Chatbot

The Camelot personal assistant for SAP MDG delivers improved usability and innovative user experience for regular and occasional MDM tasks. No end-user training and support is required as the chatbot will guide the user and answer MDM and tool related questions via a text and voice interface.

The ready-to-deploy integration framework by Camelot leverages state of the art solutions from SAP and IBM.

Logistics: Loading Meters

Logistics: Loading Meters

Camelot AI-based loading metering aims to improve accuracy in barely predictable business environments. In this way, companies achieve lower logistics costs and smoother logistics processes.

As one of several solution architectures, Camelot establishes a connection between transport management systems like SAP TM and AI services.

Self-adjusted supply chain: Dynamic process mapping by AI Camelot’s solution for a self-adjusted supply chain is build on the Camelot AI Composer and SAP Leonardo. It delivers value by linking business and data. The AI Composer enables an automated mapping of value to process steps within supply chain planning.
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Service Offerings

Camelot’s AI service offering spans the full range of advisory, educational, and implementation services with the overall goal to enable companies to perform smart decisions based on their data.

Artificial Intelligence Educational and Advisory Services

AI Executive Briefing
AI Ideation Workshop
AI Roadmap Design
AI Basics Training

Artificial Intelligence Implementation Services

AI Enterprise Solution Integration
Prototype Development
Integration Services
AI Composer


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