Senior-led delivery
Every North Shore engagement is led by a senior consultant — no junior pipelines, no resold capacity. New Zealand clients deal directly with the operators doing the work.
AI Governance & Risk for New Zealand organisations operating in and around North Shore. AI governance that engineering teams will actually use — model and dataset inventory, risk tiering, red-team requirements per tier, and approval workflows that do not become the AI bottleneck. Mapped to NIST AI RMF and ISO/IEC 42001 where it matters.
The finance, tech, healthcare concentration around North Shore sees wire-transfer fraud, instant-payment abuse and identity-driven account takeover. Our ai governance & risk work in Auckland is scoped against this real threat profile, not a generic checklist.
Every finding ships with a control reference against NZ Privacy Act 2020 and NZISM, with GCSB / NCSC NZ guidance cited where it changes the remediation priority. Board reporting follows the CERT NZ Critical Controls expectation set.
Basalt delivers ai governance & risk to organisations across North Shore and the wider Auckland region (population ~275k). The finance, tech, healthcare sectors that anchor the region face a distinct threat profile — wire-transfer fraud, instant-payment abuse and identity-driven account takeover — and our engagements are scoped to that, not a generic playbook. Reporting maps cleanly to the NZ Privacy Act 2020 and NZISM that New Zealand boards already use, with regulator context (GCSB / NCSC NZ) called out where it changes a remediation priority.
Every North Shore engagement is led by a senior consultant — no junior pipelines, no resold capacity. New Zealand clients deal directly with the operators doing the work.
Findings and roadmaps reference the regulatory environment your business actually operates in — NZ Privacy Act 2020 and NZISM. Board-level reporting follows the CERT NZ Critical Controls expectation set, so what we deliver lands without translation.
We actively research and test agentic AI tool-abuse and indirect prompt injection at scale, MCP server and AI-tool supply chain compromise and post-quantum cryptographic readiness (NIST PQC migration) — attack paths most regional providers still haven't mapped. Forward-thinking cyber defence, not last year's playbook.
Cyber security in New Zealand can't be done with last year's threat models. The Basalt practice runs against current attacker tradecraft — agentic AI abuse, MCP and AI-tool supply chain, post-quantum readiness — alongside the legacy infrastructure work that still keeps most organisations awake at night.
Most North Shore engagements scope inside one week and start within two. Retainer clients can trigger work the same day. We do not pipeline New Zealand clients through junior teams — a senior consultant scopes and runs the work end-to-end.
Both. Sensitive work — classified-adjacent environments, live incident response, OT walkthroughs — gets on-site time in North Shore and the wider Auckland region. Routine assessments and detection engineering run remote with a tight feedback loop.
Every finding ships with a control reference against the NZ Privacy Act 2020 and NZISM so your compliance team is not re-mapping our report. Where GCSB / NCSC NZ guidance exists for the specific finding, we cite it inline. Board-level reporting follows the CERT NZ Critical Controls expectation set.
The finance sector concentration in North Shore drives a different threat model than a generic New Zealand engagement — wire-transfer fraud, instant-payment abuse and identity-driven account takeover. Our scoping reflects that, and so does the test library we bring to the work.
Yes — this is core to how we work. Basalt actively researches and tests against agentic AI tool-abuse and indirect prompt injection at scale, MCP server and AI-tool supply chain compromise and identity-first attack chains across federated SaaS. Most regional providers haven't mapped these attack paths; we run them in production against client systems with explicit scope.
Strategic cyber security consulting
Adversarial testing for LLMs and AI systems
CREST-aligned penetration testing
Source code review and SAST/DAST integration