Responsible AI and AI Governance
Implement AI projects with clear decisions and responsibility.
Which AI applications are in use, who approves them and how are their effects assessed? We help translate these questions into practical procedures. An application inventory, clear roles, evaluation and recorded decisions connect innovation with accountable use. We begin with your actual projects and the people responsible for them.
Your options
Services that move your project forward
Capture AI applications and goals
Planned and existing applications are recorded with their purpose, users, data and owners. External services and internally developed components are documented clearly.
You will receive a reliable overview for further decisions.
Organize roles and approvals
Departments, development, IT operations, information security and other responsible functions are given clear tasks. Decision-making powers and escalation are adapted to your organization.
Projects have an understandable path from the idea to use.
Assess impacts and risks
We examine the business use, possible consequences of errors, affected people and relevant data. Mitigations and open decisions are documented within the agreed scope.
Evaluations lead to specific tasks and comprehensible decisions.
Design quality checks and human oversight
We work with users to define suitable criteria, test cases, clarification steps and approvals. People assigned to review or intervene must have the practical ability to do so.
Responsibility is built into the workflow.
Connect documentation and evidence
Purpose, data sources, components, tests, decisions, and changes are brought together. Existing management and development processes are put to good use.
Information can be found for approvals, operations and subsequent reviews.
Establish team guidance and ongoing review
Teams receive task-related orientation on usage, limits and reporting channels. Changes, new applications and experiences trigger appropriate reviews.
Governance remains linked to the actual use of AI.
Where to start
Responsible AI and AI Governance Use cases
Three example situations show how we can help.
Multiple teams deploy AI services without a common view
We document applications, ownership and the decisions that need to be made.
An AI pilot needs a documented approval decision
Purpose, data, results and open questions are transferred into a specific evaluation and decision-making process.
Existing policies are difficult for product teams to apply
We translate relevant specifications into tasks, tests and responsibilities within development.
From requirements to results
A clear process with agreed milestones
Record applications and responsible people
We choose the first scope and record existing rules and decision-making paths.
Design assessments and procedures
Roles, criteria, measures and approvals are coordinated with the responsible functions.
Test the approach on a project
A concrete use case tests whether the documentation and decision process work in practice.
Agree on maintenance and expansion
Outcomes, responsibilities, training needs, and other applications are prioritized.
Your benefit
What you receive
- A structured overview of the agreed AI applications.
- Defined roles, approval steps and documented decision-making paths.
- Application-oriented assessments with measures and open points.
- Proven templates and procedures for evaluation, documentation and ongoing review.
Ways to work with us
Choose a starting point that fits your needs. We agree the scope and required effort in a tailored proposal.
AI governance assessment
For orientation: applications, roles, existing procedures and next decisions.
Request a quote: AI governance assessmentPilot governance on an AI project
For specific implementation: assessment, approval, documentation and responsibilities.
Request a quote: Pilot governance on an AI projectExtend AI governance
For multiple teams: reusable procedures, team guidance and periodic review.
Request a quote: Extend AI governanceSYNEDAT PLATFORM
Platform experience for your project
We use these selected tools in SYNEDAT PLATFORM or its delivery processes. We adapt suitable practices to your project and align their integration with your existing systems.
Identities, secrets and policies
Keycloak · OpenBao · External Secrets · Kyverno
Sign-in, technical secrets and platform policies serve different purposes. We connect them with roles, limited permissions and documented exceptions. The selected tools form part of a common access and operating model.
Controlled access and more consistent platform policies.
Observability and operations
Prometheus · Grafana · Alloy · Loki · Tempo
Metrics, logs and traces provide different views of applications and platforms. We organize data sources, dashboards and alert paths around specific operating questions. Retention, sensitive data and costs are considered when planning data collection.
Better incident diagnosis and informed operating decisions.
Data, search and messaging
MySQL · Redis · RabbitMQ · Solr · OpenSearch
Data storage, caching, messaging and search have different consistency, access and recovery requirements. We select and connect these components around your business processes. Ownership and maintenance are part of the integration.
Technical components that fit your data and application processes.
Questions before you get started
What does Responsible AI encompass in a project?
It combines purpose, quality, impact and responsibility with specific development and operational tasks. The scope depends on actual use. We design verifiable procedures and documented decisions for the teams involved.
Does every AI project have to go through the same approval process?
The required scope depends on usage, data, impacts and applicable requirements. A comprehensible initial assessment helps to determine appropriate tests. Decisions and the responsibility for them are explicitly documented.
How do you take the EU AI Act into account?
We support the technical and organisational inventory and implementation of agreed requirements. Legal classification depends on factors including your role and the use case, and is clarified with the responsible legal and compliance functions. The project service does not establish blanket conformity with the regulation.
What role do existing management systems play?
Information security, data protection, quality management and software development often already contain suitable processes. We combine AI-specific tasks with these basics. Additional procedures are added where specific gaps exist.
How is human control designed in practice?
The people responsible need understandable information, sufficient time and effective ways to intervene. Approvals, clarification requests and error handling are tested in the actual process. Oversight needs to work in practice, beyond a formal confirmation step.
Can you investigate discrimination risks or unreliable results?
Suitable tests depend on the task, data, affected groups and available references. We support technical evaluation and document the limits of what it establishes. Business assessments and decisions remain assigned to the responsible people.
Does this require a specific governance tool?
Not necessarily. Existing documentation, ticketing and development tools can provide a starting point. Tool selection follows the required evidence, access and maintenance tasks. Organisational responsibility still needs named owners.
How does governance remain effective after implementation?
New applications, changed data, model changes and incidents need defined reporting and review procedures. Named owners and regular reviews keep the inventory current. Agreed support can assist with maintenance and team training.
Discuss your next step
Which AI project needs a clear decision now?
Describe the application, stakeholders and open questions. We propose a practical starting point for assessment and governance.
Responsible AI and AI Governance
Your next step
Tell us what you need. We will route your enquiry to the right team and discuss the next steps with you.
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