LLMs that stay inside your walls
Run large language models safely within your enterprise ecosystem.
Why on-prem
Your data, your rules
Why enterprises choose on-prem GenAI:
- 01
Full data sovereignty & governance
- 02
No risk of API token leaks or 3rd-party retention
- 03
Tailored hardware optimization (GPU, CPU, RAM)
- 04
Works in air-gapped and regulated environments
- 05
Zero egress costs, no per-token fees
What we deploy
From model to stack
Calsoft builds complete on-prem LLM stacks:
Infrastructure planning
We size it right
We analyze:
Security & governance
Compliant by design
We enforce:
- RBAC and ABAC policy hooks
- Token-level and context window audit logging
- Prompt injection shielding and response filtering
- Red-teaming for adversarial prompt resilience
- Encryption at rest + runtime + in vector search
- Full isolation via VPC or on-prem cluster
Need GenAI without sending data outside your walls?
Outcomes delivered
Here’s how we get started
Compliance readiness
Cost per 1M tokens
Network dependency
Downtime risk
Customization depth
How to start
Deploy in 4 steps
Define the use case
Identify high-sensitivity GenAI needs (e.g., healthcare, banking, defense).
Select the stack
Choose open-source model, embedding method, vector DB, and serving layer.
Plan the infra
Estimate GPU, memory, storage needs; configure HA and failover.
Deploy + monitor
Launch in your secure environment, integrate with tools, and govern usage.
