Deploy context-aware AI agents that understand relationships and workflows, working together to solve complex business challenges.
Open Architecture
On-premise, cloud, or hybrid - your data, your choice, no vendor lock-in. Complete flexibility for enterprise deployment.
Unified Context Platform
Connect all your data sources into a unified knowledge graph that AI can understand and leverage.
Why C64AI?
Dimension
Structure Preservation
Engineering-Grade
Production Agents
Time to Value
LLM Agnostic
European Sovereignty
C64AI
Full hierarchy & relationships
Built for PLM, ERP, CAD, est data
Execute workflows, not just retreive
Weeks with Vertical Kits
Any model, swap anytime
Austrian, GDPR-aligned
RAG Platforms
Flattened to vectors
Document-focused
Retreival only
Months of tuning
Often locked in
Mostly US-based
Data Catalogs
Metadata only
Schema-focused
No agents
Months of setup
N/A
Varies
Custom Development
Depends on build
Depends on build
Custom effort
12-18 months
Depends on build
Depends on hosting
Powerful AI Models Aren't Enough
AI models are everywhere. Structured data, the ground truth of AI is not. That's why 95% of enterprise AI never reaches production. The bottleneck isn't the model. It's the missing context.
Context engineering closes this gap. Not better prompts, better context: your data, your business logic, your workflows, connected into a layer AI can reason with and act on.
$120B
Of enterprise AI initiatives stall because they don’t connect to real workflows and structured data.
- Jensen Huang, NVIDIA GTC 2026
7x
Productivity increase in test case generation using knowledge graph-driven, workflow-aligned agents
65%
Using a context-driven approach, search and rework in a German OEM environment were reduced by 65%, unlocking millions annually.
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