Cybersecurity Services & AI Engineering

Cybersecurity compliance services connect regulatory requirements to what your cloud environment enforces. SiegePal runs readiness assessments and gap analyses across the frameworks that matter most to cloud-native and regulated businesses. Each engagement produces a remediation roadmap engineers can act on directly.

• Compliance Assessments

  Readiness reviews, gap analysis, and audit preparation across HIPAA, SOC 2, ISO 27001, PCI DSS, and other required frameworks.

• HIPAA Compliance

  Risk assessments and technical safeguard verification for healthcare organizations and business associates handling PHI.

• SOC 2 Compliance

  Readiness assessments and control implementation mapped to the Trust Services Criteria, preparing SaaS and technology companies for their CPA audit.

• ISO 27001 Gap Assessment

  Annex A gap analysis, ISMS scoping, and Statement of Applicability work verified against live AWS, GCP, and Azure infrastructure.

• PCI-DSS Compliance

  Scoping, gap assessment, and remediation for merchants and service providers handling cardholder data, assessed against the PCI DSS v4.0 baseline.

• vCISO

  Fractional security leadership covering strategy, risk management, board reporting, and compliance oversight for organizations that need a named security owner.

Cloud security services at SiegePal cover the full lifecycle: architecture, monitoring, incident response, and vulnerability remediation. Coverage spans AWS, GCP, and Azure. Each service is checked against your cloud setup, catching IAM drift, encryption gaps, and misconfigurations a policy review would miss.

• Cloud Security Engineering

  Architecture design and implementation covering zero-trust networks, IAM federation, encryption and key management, and DevSecOps pipeline integration.

• Incident Response

  Incident response for active or suspected breaches, including containment, forensics, and ransomware response, with retainer options available.

• Security Monitoring

  SIEM operations, detection engineering, and security monitoring that turns raw cloud log data into alerts your team can act on.

• Vulnerability Management

  Continuous scanning, risk-based prioritization, and DevSecOps pipeline integration that catches vulnerabilities before they reach production.

• Cloud Posture Management

  Configuration assessment, IaC security, and drift detection across multi-cloud environments, benchmarked against CIS controls and applicable compliance frameworks.

Security testing services validate whether your defenses hold up against a real attacker, not just a checklist. SiegePal's testing is manually led, with findings scoped to your actual attack surface and business risk.

• Penetration Testing

  Manual, expert-led testing across web applications, networks, mobile apps, and cloud infrastructure, with proof-of-concept evidence and remediation guidance.

• Risk Assessment

  Structured evaluation of organizational risk using qualitative and quantitative methods, including threat modeling and third-party vendor risk analysis.

AI engineering work at SiegePal applies the same architecture-first discipline used in cloud security. Access controls, audit logging, and human-in-the-loop review are designed in from the start.

• AI Engineering

  Design, build, and deployment of production AI systems, including autonomous agents, frontier model integrations, custom-trained models, and AI workshops.

• AI Agent Implementation

  Multi-agent architectures with least-privilege tool access, human-in-the-loop controls, and audit logging built into the system from day one.

• AI Integrations

  Production integrations with OpenAI, Anthropic Claude, Google Gemini, and open-source models, including RAG pipelines and workflow automation.

• AI Workshop & Playbook

  Executive workshops that map AI opportunities across your business and deliver a governance framework and implementation roadmap.

• AI Model Training & Hosting

  Fine-tuning foundation models on proprietary data, with hosting on AWS, GCP, or Azure and MLOps tooling for monitoring.

• AI Security

  LLM red teaming, RAG pipeline security, and agent security assessments that test for prompt injection, data leakage, and tool abuse.