AI Consulting
LLM · RAG · Agents · Governance
ExploreFrom LLM, RAG and agent architectures to penetration testing; from secure-by-design software and IoT to ISO 42001 AI governance, we design, test and deploy critical systems through an attacker-informed lens.
✓ PII redaction active
✓ prompt injection blocked
! human approval required
01 Prompt Injection
02 Data Leakage
03 Model Abuse
AI, cybersecurity and product engineering operate through the same threat model, evidence chain and production discipline.
We manage data, models, agent authority, cost and regulation in one delivery plan.
We map data maturity, use cases, team capacity, regulatory impact and the ROI/risk landscape together.
Every service connects to a real detail page, standards, deliverables and a closure approach.
Bring PoCs, LLMs, RAG and agent systems together with security, governance and production discipline.
Make AI governance measurable and auditable across the EU AI Act, KVKK and ISO 42001.
A risk-led, actionable security roadmap from current state to target architecture.
Validate real attack paths with OSINT, manual exploitation, lateral movement and included retesting.
Assess identity, session, API and business logic risks through manual testing and retesting.
Test identity, authorization, data protection, audit and operating system layers together.
Manage ST/PP, EAL targets and laboratory coordination under ISO/IEC 15408.
Unite legal requirements with data inventory, technical controls and breach readiness.
Build enterprise platforms, web, mobile, APIs and AI automation through secure product engineering.
Build secure boot, identity, signed firmware and controlled OTA from device to cloud.
Every step from scope to retest has a concrete deliverable and decision owner.
Scope document + risk map
Attack surface + priority
PoC + logs + visual evidence
Remediation plan + KPI
Closure evidence
Engineering must see and understand beyond the horizon.
For critical systems, we design for tomorrow’s attack and regulatory surface, not only today’s findings.
The product team needed a technical roadmap for ST/PP, evaluation evidence and laboratory coordination.
A scope, threat model, manual validation, remediation and retest chain was applied.
13+ hands-on programs with active consultants and testers, isolated labs, certificates, 30-day lab access and post-training support.
scenario: enterprise_rag_boundary
source_integrity: PASS
malicious_context: DETECTED
unsafe_retrieval: BLOCKED
audit_event: SIGNEDA starting checklist for personal data, model inventory and audit trails in AI systems.
5 min readA practical view of prompt, data, agent authorization and output risks in LLM applications.
7 min readCompare how scope, methodology and evidence expectations work together.
6 min readWe bring penetration testing, security architecture, AI/LLM security and IoT/embedded expertise into one project room.
Meet Kritera→Let us put the use case, data posture, attack surface and compliance target on the same table.