AI & Knowledge Systems
AI that can work with your business, not around it.
We design private and hybrid AI systems that connect models to company knowledge, applications and workflows while keeping architecture, access and data boundaries explicit.
Beyond the chatbot
AI is an architectural layer, not a product demo.
A useful AI capability touches model access, retrieval, permissions, integration and evaluation. We treat all of them as engineering disciplines with the same rigour as infrastructure.
- Model access: local inference and external model APIs
- Enterprise search, RAG, embeddings and vector search
- Document processing and workflow automation
- Agents with controls, evaluation and observability
- Access control, usage limits and cost governance
Reference architecture
Data, retrieval, models, applications — one pipeline
Permissions are resolved before retrieval. Routing decides where a request goes. Governance covers every hop.
Capabilities
What an AI system consists of
Private AI
- Run suitable AI workloads inside company-controlled infrastructure
- Data boundaries stay explicit and internal
Hybrid AI
- Combine local data processing with selected external models
- Use external capability where it creates a clear advantage
RAG & enterprise knowledge
- Connect LLM systems to documents, policies and knowledge bases
- Business data and project information via vector search where appropriate
Model routing
- Route workloads by cost, privacy, capability and latency
- Context size and task type considered per request class
AI agents & workflows
- Controlled steps: classify, extract, summarize, route, prepare
- Actions triggered inside defined boundaries — not unattended autonomy
AI evaluation
- Answer and retrieval quality measured continuously
- Hallucination risk, latency, cost and failure modes tracked
AI is most valuable when it becomes part of a workflow — not another isolated application.
The model is only one component. Data access, permissions, retrieval, integration, evaluation and operations determine whether the system becomes useful in production.
Typical applications
Where AI earns its place
Examples of use cases we design for — an indication of the territory, not a claim that every one has been delivered.
Internal knowledge assistants
Document analysis
Contract and document extraction
Support triage
Research assistants
Sales research
Business intelligence summaries
Internal enterprise search
Developer assistance
Multilingual content processing
Automated classification
Workflow agents
Knowledge discovery
Security and infrastructure analysis
AI & Knowledge Systems
Have an AI use case in mind?
Describe the workflow, the data involved and the outcome you expect. We will map the architecture honestly — including the parts AI should not touch.