Security & Infrastructure
Building the zero-trust boundaries and reviewable configurations required to safeguard enterprise assets and customer privacy.
Four Pillars of System Safety
We integrate cryptographic protection and programmatic validation at every step of the AI lifecycle.
Contextual AI Firewall
We deploy deep semantic firewalls at the API boundary. Moving beyond static regex keyword blocks, our firewalls utilize micro-language-models to detect and block prompt injection payloads, context-overflow attacks, and malicious system override attempts before they hit your model.
Cryptographic PII Tokenization
Protect customer privacy programmatically. Before raw data is serialized or sent to external model APIs, our tokenization layer identifies, extracts, and cryptographically tokenizes sensitive PII (emails, IC numbers, credit card numbers), re-injecting the real data only when responses return to your secure database boundary.
GitOps Infrastructure-as-Code
Manage all model routings, API configurations, and deployment boundaries using reviewable Git repositories. Every route modification, parameter adjust, or container update is codified in reviewable YAML configurations, ensuring perfect system auditability and simple recovery.
Automated Sanitization Workflows
Safe database cloning for developer teams. Our sanitization pipelines parse production database clones, programmatically masking proprietary financial figures, patient records, or internal identifiers. This allows developer teams to work with realistic, structural mock-data without exposing production secrets.
The Jampuk Intelligence Shield Simulator
See exactly how Jampuk Intelligence's real-time security boundaries and cryptographic filters safeguard your LLM inputs and prevent exploits in micro-milliseconds.
Git-Driven Deployment Configs
All AI gateways, model routes, and API endpoints are declared inside standard YAML configuration files versioned in Git.
This approach prevents configuration drift, satisfies strict enterprise SOC2 audit trails, and allows deployment teams to instantly roll back a model gateway or update context-boundaries using standard pull request reviews.
apiVersion: jampuk.com/v1alpha1
kind: AIGatewayRoute
metadata:
name: document-intelligence-route
spec:
modelEndpoint: "azure-openai/gpt-4o"
security:
aiFirewall: true
piiTokenization:
enabled: true
maskFields: ["email", "ic_number", "phone_number"]
telemetry:
prometheusMetrics: true
traceDestination: "weaviate/audit-index"Secure Your Critical AI Infrastructure Today
Speak directly with AI steward & systems architect Hafiz Zainudin to audit and plan zero-trust security integrations for your enterprise database and model APIs.