Haink embeds security into the development process rather than bolting it on — Secure SDLC, SAST/DAST, SBOM, IAM and continuous assurance — and supports compliance with ISO 27001, SOC 2 and GDPR. For AI we add LLM-specific defenses and private, air-gapped deployment options.
Threat modeling, secure design and code review embedded across the development lifecycle.
Static and dynamic analysis, dependency scanning and software bills of materials in CI.
Controls, evidence and processes aligned to ISO 27001, SOC 2 and GDPR.
SSO, least-privilege access and secrets management across applications and infrastructure.
Hardened cloud and Kubernetes configurations, image scanning and runtime policies.
Prompt-injection defenses, data governance and guardrails for LLM and ML systems.
Typical stack:
Production work delivered by our engineering team. Client names withheld under NDA; sectors shown to indicate context. See full case studies →
Document authenticity, liveness and behavioral analysis cut fraud while raising conversion — security engineered into the product flow, not bolted on afterwards.
On-premises and air-gapped deployments for regulated data, with Secure SDLC, SBOM and SSO/IAM applied throughout — so sensitive data never leaves the network.
Yes. We implement the technical controls, evidence and processes aligned to ISO 27001 and SOC 2, and work alongside your auditors.
Security built into every stage of development — threat modeling, secure design, code review, SAST/DAST and dependency/SBOM scanning in CI — rather than a one-off audit at the end.
Yes — prompt-injection defenses, output validation, data governance and access controls specific to LLM and ML applications.
Yes. We deliver on-premises and air-gapped deployments for regulated data, with IAM, secrets management and auditability throughout.
Yes — data mapping, consent, minimization, retention and access controls aligned to GDPR requirements.
Let's shape a clear plan with milestones, architecture options and an implementation roadmap — with right-sized GPU hardware if AI workloads are involved.