Expertise
Integrate AI applications. Plan for operations.
We build the technical foundation for AI in your business: integrated workflows, custom applications and suitable infrastructure. Data access, API integration, identities and operations are designed together. We test critical assumptions early and support delivery through the agreed operational handover.
Some tasks suit a clearly defined workflow; others benefit from an assistant or agent with limited tool access. The task guides the architecture. Our strategic AI adoption service connects engineering with business objectives, organisational rules and team enablement.
Services
From integration to the operating model.
Example requirement. An assistant for internal documents should only use content the person asking is allowed to read. We account for the permission model during integration and also test requests in the pilot where access must be denied.
Basis for a decision
You have a use case but no clear architecture yet. We assess data, permissions, solution options, costs and the operating model. You receive an architecture concept with reasoned decisions, an implementation proposal and verifiable quality criteria.
Deliver a workflow or application
We build the agreed workflow, application or integration with your systems. A pilot tests open assumptions. Further implementation includes agreed tests, documented data flows and approvals.
Preparing for production
We add the agreed foundations for deployment, monitoring, access control and incident handling. Documentation and handover clarify who operates the service and how changes are reviewed. Production approval follows the criteria agreed together.
Technologies
What we work with here.
Models
- Claude
- OpenAI / Azure OpenAI
- Mistral
Local operation
- Ollama
Tool access
- Model Context Protocol
All product and company names mentioned are trademarks of their respective owners. Naming them describes technologies we use and implies no partnership with or endorsement by the trademark owners.
Evidence
What we stand on here.
Our foundation is experience from product development and securing AI workloads. We assess suitability for your use case in a scoped pilot.
Agent architecture from product development
Experience with agent architecture and model operations informs our technical consulting. One example is the development of Venedy, an API DAST platform in its pilot phase.
Venedy is developed by Venedy GmbH, a legally separate company with the same shareholders as Hueskotech.
Workshops for adoption and development
Our workshop offerings support development teams and decision makers in using AI at work and in addressing selection, approvals and governance across the business.
AI security as a focus
Securing AI workloads is one of Lukas Hügle’s focus areas. Data access, permissions and controlled tool calls are therefore considered in the design from the start.
Workshops
Related workshops.
AI for Engineering Teams
AI tools in daily development work: working modes, context, agents and a written team agreement.
AI for Business
A basis for decisions instead of a tool demo: what AI realistically delivers, which risks it brings, and what an approval looks like.
Secure AI
What happens when a model is allowed to operate tools, and how to limit the damage.
Insights
Further reading.
What is an AI agent in the enterprise?
A language model that may operate tools: what separates it from an assistant and why the permission question comes before the model question.
Read the article →Securing MCP
Confused deputy, token passthrough and the other traps of tool integration, and what helps against them.
Read the article →Internal AI assistants: cloud service or self-managed?
From the first use case to an assistant on your own data: architecture, permission model and operations.
Read the article →Contact
What task should your AI solution take on?
Describe the task, existing systems and your data and operational requirements. We suggest a suitable starting point: an architecture review, a focused trial or implementation.