AI Innovation Service

Agile AI Innovation – from Use Case to Operation

We use AI where it creates real business value. Together, we identify relevant use cases and develop the right solution approach – from Generative AI and intelligent AI Agent to Machine Learning and traditional automation.

Whether Azure, AWS, or a customized IT environment: we support the entire journey from idea and prototype to implementation, secure operations, and continuous improvement of your AI solutions and agents.

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Agile AI Innovation

Method

From Idea to Production-Ready AI Solution

We bring AI use cases into real-world application quickly: validate early, implement with focus, learn in production, and scale.
From the very beginning, we combine business, technology, security, and operations.

Our Principle

Start small. Learn fast. Scale securely.
This way, we do not create isolated AI prototypes, but solutions that deliver measurable value and can be sustainably integrated into the organization.

Discover the Use Case

1. Alignment & Big Picture

Sharpen the use case, target vision, and expected value. We clarify requirements, constraints, and success criteria.

Design of architecture & POC

2. Proof of Concept

Assess feasibility and reduce risks. We test data, models, integration, and the solution approach under realistic conditions.

Development of an MVP

3. MVP-Definition & Kick-off

Focus on what is truly needed. We define the production-ready MVP and prioritize implementation.

Deploy & Refinement

4. Go-Live & Refinement

Go live and learn from real-world usage. The solution is launched and continuously improved based on quality, feedback, and results.

Scale & Continuous Improvement

5. Scale & Improvements

Scale successful solutions. We expand usage, functionality, and application areas while continuously optimizing the solution.

AI that delivers real impact in everyday work

Use Cases

AI creates real value when it takes on specific tasks, reduces workload for employees, and improves existing processes. The following use cases show how companies can already apply AI across different business functions today – securely, seamlessly integrated, and tailored to the needs of the organization.

The solutions can be implemented as standalone use cases or integrated as reusable building blocks within the como Capability Hub.

Use Case 1

Conversational AI

Intelligent Support for Service Desk and IT Conversational AI supports employees and service teams with recurring requests and ensures that information reaches the right place faster. The AI understands requests in natural language, automatically classifies them, and accesses existing knowledge, documentation, and solution descriptions. This allows standard requests to be answered directly, solution recommendations to be generated, and more complex cases to be routed to the right experts. The value: faster response times, less manual ticket handling, and significant relief for the service desk.

Use Case 2

Knowledge Base Expert

Make Enterprise Knowledge Intelligently Accessible Information is often spread across documents, presentations, wikis, policies, and business systems. The Knowledge Base Expert makes this knowledge available through a central AI-powered access point. Employees can ask questions in natural language and receive specific answers based on approved company information, including references to the underlying sources. This transforms a traditional document repository into an actively usable knowledge base. The value: less time spent searching, faster answers, and significantly improved access to existing enterprise knowledge.

Use Case 3

AI Avatar in Sales

Scale Personalized Customer Engagement AI avatars open up new possibilities for personalized yet scalable customer communication. Based on defined content, personalized presentations, product introductions, or sales messages can be created. Content can be dynamically adapted to the target group, customer, industry, or specific sales context and delivered, for example, as a video, digital point of contact, or part of a sales process. By connecting existing CRM, content, and knowledge systems, companies can create new forms of customer engagement. The value: more personalized communication, more efficient content creation, and new digital touchpoints in sales.