Enterprise Security
PrivateAIModelDeployment
Worried about public AI APIs leaking secrets? We build fully controllable on-prem LLM environments on K8s. Data never leaves your network.
Security is Non-Negotiable
Public AI APIs are convenient but pose significant risks for enterprise intellectual property. Our Private AI solution ensures your data never leaves your VPC.
Data Sovereignty
Complete control over training data and inference logs.
Compliance Ready
Meet GDPR, HIPAA, and internal security audit requirements.
Your Firewall
Secure Intranet Zone
Enterprise Data
→
Private LLM
→
Secure API
* Data never leaves your infrastructure
How private deployment works: staged delivery
Keep data in your hands first, then increase on-prem inference over time.
Stage 0
Private data + cloud inference
Docs/vector store/logs stay on your side; inference calls cloud models with minimal context.
Stage 1
Local embeddings + cloud model
Embeddings run inside your network; cloud models only receive necessary snippets.
Stage 2
Local embeddings + local LLM
Inference also runs on-prem, with observability, audit, and cost controls.
How to validate reliability
Isolation and access control: prevent cross-tenant or cross-org leakage
Prompt red-team & boundary testing: reduce hallucination and overreach answers
Citations and eval-set regression: traceable answers and continuous improvement
Boundaries we commit to
We do not promise “magic private AI”. We promise staged delivery, verifiable security and usability, with explicit cost and performance constraints.