Local & hybrid LLMs
Deploy models close to your data with hybrid cloud fallbacks for scale and specialized tasks.
Solution
Artificial Intelligence
Local LLM integration, automation, and decision intelligence for enterprises that need control over data, latency, and operations.
Overview
Built for operational outcomes
Cibernetica designs AI systems that connect to real facility, ERP, and messaging data — not isolated chat demos. We implement local and hybrid LLM architectures when residency, privacy, or offline resilience matter.
- Automate document, ticket, and operations workflows with grounded context
- Keep sensitive data on controlled infrastructure when required
- Connect AI outputs to ERP, dashboards, and WhatsApp Business processes
Capabilities
What we deliver
Operational copilots
Assist supervisors and operators with retrieval over SOPs, sensor history, and work orders.
Decision pipelines
Turn alerts and telemetry into ranked actions with human approval gates.
Secure integrations
Wire AI into ERP, BMS, CRM, and WhatsApp workflows with audit-friendly logging.
Architecture
How the pieces connect
- 01
Data sources
ERP, BMS, tickets, documents, IoT history
- 02
Retrieval layer
Grounded context with access controls
- 03
Model runtime
Local, hybrid, or approved cloud endpoints
- 04
Action layer
Dashboards, approvals, WhatsApp, work orders
Technology signals
Local LLM runtimesRetrieval pipelinesVector indexesAPI gatewaysERP connectorsOperator UIs
Engagement
01
Discover
Map facilities, systems, and operational goals across your sites.
02
Design
Architect connectivity, AI, and software around your existing stack.
03
Deploy
Install sensors, gateways, integrations, and operator-ready interfaces.
04
Operate
Monitor, optimize, and evolve with measurable business outcomes.
FAQ
Solution questions
Next step
Tell us about your facilities, systems, and goals. Submissions are emailed to hello@ciberneticatech.com. You can also call 01 895 441 or 76 523 441.
Cibernetica SARL · Al Anwar Street, Kassouf Plaza, Stage 9, Jdeideh
Consultation form
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