Solutions & Services · AI Security & Guardrails
Agents act on behalf of your business. Make sure they can’t act against it.
LLM applications and autonomous agents introduce a new attack surface: prompt injection, data exfiltration through tools, jailbreaks, over-privileged actions and silent quality decay. Kimbodo reviews, hardens and monitors AI systems — yours or ones we build — with the NemoClaw™ Secure Agents methodology: threat modeling, layered guardrails, red-team evaluations and audit-grade logging.
What Kimbodo Delivers
Review
Know your AI attack surface before someone else maps it.
- Threat model across prompts, tools, data and actions
- Prompt-injection and jailbreak testing
- Permission and data-access audit of agent tools
- OWASP LLM Top 10 assessment with prioritized findings
Harden
Layered guardrails that hold up in production.
- Input/output filtering and content policies
- Least-privilege tool permissions and scoped credentials
- Human approval flows for consequential actions
- PII redaction and data-boundary enforcement
Monitor
Security is a process, not a launch checklist.
- Continuous red-team evaluation suites
- Audit-grade logging of prompts, retrievals and actions
- Anomaly detection on agent behavior and spend
- Incident-response runbooks for AI-specific failures
Timeline & Engagement Model
A focused security review of one AI application takes 2–4 weeks and ends with a prioritized findings report. Hardening programs run 4–8 weeks. Continuous monitoring is a monthly subscription. The full methodology is productized as NemoClaw™ Secure Agents.
Proof, Not Promises
- AI-powered legal knowledgebase bot — governed retrieval with approved-answer controls in a confidentiality-critical domain
- Automated compliance audit for medical-services websites and ads — AI applied inside a regulated industry’s constraints
- AI-powered talent & employer chatbot with human escalation — human approval flows on consequential AI actions
Buyer Questions
We didn’t build our AI system with you. Can you still review it?
Yes — most security reviews are of systems built in-house or by other vendors. We need read access to the architecture and a test environment; findings are delivered with concrete fixes your team (or ours) can implement.
What does an AI security review cost?
Focused reviews typically start around $15,000; hardening programs for multi-agent or regulated systems usually land between $25,000 and $85,000. The estimator gives you a range for your system in about a minute.
Do guardrails make the assistant useless?
Badly designed ones do. We tune guardrails against evaluation suites so refusal rates on legitimate requests stay measurably low while blocked-attack rates stay high — you see both numbers before and after hardening.
Find the holes before production does
Describe your AI system; get a preliminary review scope, range and timeline immediately.