Every day, companies create large volumes of data from invoices, emails, CRM systems, time tracking, and support tickets. Most of that data stays spread across disconnected tools, which turns valuable knowledge into isolated fragments.
Data lake and data mesh as the foundation
To unlock this potential, organizations need a clear data architecture.
data products with clear responsibility and quality.
- A data lake centralizes structured and unstructured data in raw form.
- A data mesh assigns domain ownership, so business teams manage their own
Combined, both models provide reliable and current data for AI workloads.
LLMs and SLMs: broad capability plus precision
LLMs are strong general-purpose language models that support writing, summarization, contextual email handling, and code or report generation.
SLMs are specialized models trained for specific domains where accuracy is critical, such as technical diagnostics, internal knowledge systems, or clinical documentation.
Using both together gives companies flexibility and precision at the same time.
Agentic AI: from reading information to executing work
AI agents use LLMs and SLMs to retrieve company data and complete tasks autonomously.
- Invoice matching against ERP purchase orders and payment terms
- Automated customer support responses grounded in CRM and wiki data
- Project controlling with early risk signals from budget and milestone data
- Onboarding support tailored to each role across HR and internal tools
This turns AI from a passive assistant into an operational teammate.
Local hosting or external hosting
Local hosting offers stronger data sovereignty, compliance control, model customization, and often lower latency for internal workflows.
External cloud hosting is faster to start and easier to scale, but can add privacy concerns, lock-in risk, and less control over adaptation.
For sensitive use cases, local deployment is often the more sustainable strategy.
Conclusion
Organizations that combine local AI models, robust data architecture, and agent-based automation gain faster decisions, better efficiency, and a real innovation advantage.
If you want to consolidate data sources and deploy practical AI agents, jaraco gmbh can support your team from architecture to implementation.