Protect models and pipelines from poisoning, prompt-injection, and data leakage.
Outcomes
- Threat model specific to your AI use case
- Tested guardrails against real adversarial inputs
- Clear mitigations for code, data, and policy
What we do
- Map model/app/data flows (inputs, context, outputs)
- Red-team prompts and adversarial samples
- Data governance review (PII exposure, retention)
- Guardrail design (input/output filters, policies, RBAC)
- Logging/monitoring recommendations
Scopes we cover
- LLM chat/apps (RAG, tools/functions, agents)
- Classification/regression pipelines
- Fine-tuning & training data handling
Deliverables
- Attack paths & exploitation examples
- Guardrail & monitoring checklist
- “Break-glass” response playbook
Timeline & pricing
- 2–4 weeks; from $4,000
Add-ons
Maturity roadmap (3–6 months)
Developer training on secure prompt patterns