Operate AI applications and models with control

GSWE helps move AI prototypes into manageable application operations.

Operate AI applications

A production AI application needs observable quality deviations and defined outage handling. GSWE connects fixed test cases with monitoring and release approval. Each model change receives a traceable decision and a prepared fallback path.

Case studies

GRUEN ItexCentral metadata platform for publishers

Metadata platform for publishers focused on integration, data processing, and stable publishing workflows.

Berlin House of RepresentativesDevelopment of a web application for the Berlin Parlament

Case study on operations, security, and continuous development of a public-sector web application.

Competences

Solutions

AI Governance Platform for AI operationsAI Governance

Platform for AI operations and traceable governance of productive AI systems.

DevOps Infrastructure for Software DeliveryDevOps Infrastructure

GSWE develops DevOps infrastructures for automated software delivery, stable deployments, and scalable operations.

Operations Platform for Applications and SystemsOperations Platform

GSWE develops operations platforms for stable system operation, monitoring, and continuous optimization.

Knowledge & Retrieval PlatformKnowledge Platform

Platform for AI-supported knowledge use, document search, and structured retrieval processes in complex information landscapes.

Services

Operate AI systems and secure availabilityOperate AI systems

Operate AI systems and secure availability to control runtime behavior, scaling, and stability reliably.

Operate AI applications and ensure stabilityOperate AI applications

Operate AI applications and ensure stability to combine usage, logic, and models reliably.

Operate AI development environments and stabilizeOperate AI toolchains

Operate AI development environments and stabilize to ensure reproducible development, training, and deployment.

Plan AI adoption and assess applicationsPlan AI adoption

Plan AI adoption and assess applications to identify meaningful use cases, data requirements, and realistic paths for integration in a structured way.

Articles

Data Architecture for Scalable AI Systems

Clean data architecture is the foundation for AI, automation and scalable systems.

AI operations: quality and model changes

Operating AI models reliably: requirements for model changes, quality evaluation and integration into existing applications.

Backend architecture for AI applications

How backend architectures for AI applications are designed to enable scalability, data processing, and integration.

Data pipeline architecture for AI systems

How data pipelines for AI systems are designed to ensure stable, scalable, and high-performance processing.

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Posts

Restrict AI access before generating an answer

An assistant should receive only sources the current user is authorized to access.

Evaluate AI responses against a stable test set

One convincing example does not replace repeatable quality evaluation.

Bound AI tools with explicit approval rules

Reading, preparing and executing require different technical permissions.

Treat a model switch as an application change

New models can change response behavior, tool calls and failure modes.