Automotive: accelerate engineering, quality, purchasing, and after-sales processes.
Consulting boutique for agentic AI
Agentic AI for industrial value creation
IconicC digital develops AI agents that understand processes, use tools, and execute work reliably across industrial systems.
From strategic clarity to secure production operation.
Selected customers
Industrial focus
Where agentic AI creates measurable impact
Mechanical and plant engineering: make technical knowledge usable across complex product lifecycles.
Energy and chemicals: support operations, maintenance, compliance, and documentation with controlled agent workflows.
Semiconductors and other industries: connect expert knowledge, data, and systems for faster decisions.
Our services
From relevant use case to productive AI agent
We combine industrial process expertise, AI engineering, and implementation discipline in one senior team.
AI strategy
We define ambition, target architecture, governance, and a roadmap aligned with your business priorities.
Use case discovery
We identify and prioritize applications by value, feasibility, data readiness, and operational risk.
Agent architecture
We design secure agents, tool access, knowledge layers, orchestration, and human control points.
Engineering and integration
We implement agents and connect them to ERP, PLM, MES, CRM, data platforms, and specialist systems.
Evaluation and governance
We make quality, safety, costs, and business impact measurable and auditable before scale-up.
Enablement and scaling
We transfer knowledge, establish operating models, and help your teams scale successful agents.
Our approach
A clear path from opportunity to operation
We join at your current stage and keep value, feasibility, and production readiness connected throughout.
Understand: align objectives, processes, data, systems, constraints, and decision criteria.
Prioritize: build a realistic business case and select a use case with a viable path to scale.
Build: develop and integrate the agent in short iterations with measurable acceptance criteria.
Operate: establish monitoring, governance, ownership, and continuous improvement for production.
Ways to start
The right format for your current AI maturity
Focused, senior, implementation-driven
Begin with a compact assessment or engage us through architecture, implementation, and productive scale-up.
Strategy and use case sprint
Focus
roadmap
Agent engineering and integration
Build
to production
Built for production
Industrial AI needs more than a capable model
We design the full socio-technical system so agents remain controllable, reliable, and useful in day-to-day operations.
Human control
Clear responsibilities, approvals, escalation paths, and intervention points for critical decisions.
Security and compliance
Role-based access, traceability, data protection, and governance aligned with your risk profile.
Evaluation by design
Continuous tests for task quality, robustness, latency, cost, and operational outcomes.
Technology independence
Architecture and model choices follow the use case, infrastructure, and lifecycle instead of a preferred vendor.
FAQ
Frequently asked questions
What is an AI agent?
An AI agent combines a model with knowledge, tools, memory, and control logic to pursue a defined goal and execute multi-step work.
Where should we start?
Start with a process where information is fragmented, skilled people spend time coordinating, and outcomes can be measured.
Do we need perfect data first?
No. We assess the available data and design around its reality, while making targeted improvements where they unlock value.
Can agents connect to our existing systems?
Yes. Integration with existing APIs, databases, enterprise applications, and controlled user interfaces is central to our work.
How do you keep agent behavior reliable?
Through scoped permissions, evaluations, observability, fallback paths, and human approval where consequences require it.
Are you tied to a model or cloud provider?
No. We select models and platforms according to requirements for quality, security, cost, deployment, and maintainability.
Dipl.-Ing., MBA Robert Diab
Founder & CEO
"Agentic AI becomes valuable when it is deeply connected to real processes, reliable in operation, and accepted by the people who work with it."