SRV-01
Ticket support automation
End-to-end implementation of automated ticket resolution — system integration, knowledge-base indexing, and safety-rule configuration.
Inquire§ Services
The expertise to implement, secure, and scale.
Beyond software, we provide the engineering required to implement, secure, and scale automation within complex enterprise environments.
SRV-02
Enterprise knowledge chatbots
Internal chatbots that know your business. On-prem setup, retrieval-augmented generation pipeline, and security controls.
InquireSRV-03
Automation & workflow design
Consultancy and implementation for complex operational workflows. We map current processes and build robust automation pipelines.
InquireSRV-04
On-prem AI deployment
Safe deployment of open-weight LLMs within your infrastructure. Hardware optimization and air-gapped functionality.
InquireSRV-05
Enterprise system integration
Custom connector development for proprietary or legacy systems — the bridges that let Cressu orchestrate your entire stack.
InquireSRV-06
Knowledge optimization
Fine-tuning and curating your knowledge base for high-accuracy automation. We structure your data for machine understanding.
InquireReady to modernize your operations?
Let’s discuss your specific requirements and environment.
Implementation, answered
What managed on-prem AI deployment actually involves — from model selection to air-gapped rollout.
01How do you deploy an LLM on-premise?
On-prem LLM deployment involves selecting an open-weight model, provisioning GPU or CPU hardware inside your infrastructure, and running a serving runtime like vLLM. Cressu handles this turnkey, including air-gapped setups.
02What does a managed on-prem AI implementation include?
Cressu delivers system integration, knowledge-base indexing, RAG pipeline setup, safety-rule configuration, and workflow design — the full engineering required to ship on-prem automation.
03Can you deploy an LLM in an air-gapped environment?
Yes. Cressu packages models, runtimes, and dependencies for fully disconnected deployment, so inference runs in air-gapped or SCIF networks with no outbound connectivity.
04How long does on-prem AI implementation take?
A typical Cressu deployment takes weeks, not months, because the platform is productized rather than built from scratch. Timeline depends on integration scope and knowledge-base readiness.