Secure, monitor, and govern large language model usage across the enterprise.
Prompt injection, data leakage, and unmonitored prompt chains expose security and compliance risk.
Measurable results you can expect from our ai llm secops services.
Reduced prompt injection & leakage risk
Centralized usage visibility & audit trails
Embedded policy & content filtering
Operationalized evaluation & drift detection
Our proven methodology ensures predictable outcomes and risk mitigation.
| Phase | Objective | Key Activities | Deliverables |
|---|---|---|---|
1 Assess | LLM risk & usage map | Prompt chain inventory, data flow mapping | LLM risk report |
2 Plan | Control & monitoring design | Guardrail strategy, policy modeling | SecOps architecture |
3 Execute | Implement guardrails & logging | Content filtering, red team prompts, telemetry | Secured LLM stack |
4 Optimize | Ongoing evaluation & governance | Metric scoring, drift & anomaly detection | Governance scorecards |
Complement your ai llm secops initiative with these related services.
Let's discuss your specific requirements and create a tailored approach.