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Operating in alignment with ISO/IEC 27001 information security management principles.
AstroPema AI designs deterministic, reviewable defensive systems that operate inside the application trust boundary—where operators require direct control, auditable evidence, and verifiable enforcement without third-party telemetry dependencies.
Our work centers on the development and deployment of a self-hosted Security Operations architecture for Linux environments running web, mail, SSH, SFTP, and related services. The objective is not abstract monitoring, but structured, reproducible evidence generation derived directly from your operational logs.
Each implementation is custom-scoped to the client’s infrastructure. A standardized core architecture is deployed and then tailored to the specific topology, services, compliance posture, and operational requirements of the organization.
The core architecture may include:
Deployments can operate in multiple modes depending on client requirements:
All systems are deployed within the client’s own infrastructure. No external telemetry extraction, cloud data brokerage, or remote dependency is required. The client retains operational ownership of the deployed architecture.
Engagements are structured as architecture design + deployment projects. Ongoing support, tuning, or compliance-aligned documentation workflows may be included as separately defined service agreements.
All systems are designed to preserve operational governance: analytical tooling executes in read-only mode against security logs and telemetry, while enforcement actions remain explicitly human-directed and occur outside analytic notebook execution.
These documents demonstrate the system’s emphasis on reviewability: log → decision → expected action → verifiable enforced state.
Engagements are custom-scoped and architecture-driven. Projects typically begin with a focused threat-model and infrastructure review, followed by a time-boxed design, build, and validation phase within the client’s own environment.
If you want a custom-fit system or review, send a short note with your environment and goals. You’ll get a human reply—no lists, no automation, no follow-ups.
AstroPema AI designs, deploys, and operates complete self-hosted Linux infrastructure environments — from bare metal configuration through application delivery, security enforcement, and AI-enabled services. Our work is demonstrated through production systems actively serving real users under real operational load, not lab environments or theoretical architectures.
The following capabilities are not aspirational — they represent systems currently running in production across multiple domains including AstroPema.AI, AstroMap.AI, PemaHosting.com, and OrNeiGong.org. Every component listed below has been designed, implemented, documented, and is actively maintained by AstroPema AI.
Our primary operating environment is Debian/Ubuntu Linux, administered at a demonstrable production level across multiple servers and service domains. Core infrastructure competencies include:
A fully self-hosted email stack is operated in production, providing authenticated, deliverable mail services with active abuse mitigation:
AstroPema AI operates a local GPU-accelerated AI inference environment, eliminating API dependency costs while maintaining full data sovereignty:
Our security work centers on deterministic, reviewable defensive systems operating inside the application trust boundary — where operators require direct control, auditable evidence, and verifiable enforcement without reliance on external telemetry pipelines.
Bash scripting is central to daily operations across all managed systems. Automation is not incidental — it is how the infrastructure runs reliably without a large team:
Infrastructure operations are managed with enterprise-grade documentation discipline, supporting formal compliance objectives:
Engagements can be structured to match client requirements and operational context:
We design and maintain web-based applications from front-end presentation through backend logic and database persistence. Production deployments include:
MIT IDSS Machine Learning & Deep Learning | CMU Deep Learning — top 2% both cohorts.
BS Mathematics & Computer Science, University of Puerto Rico.
40+ years spanning electronics, telecommunications, Silicon Valley network
infrastructure, and enterprise Linux administration.
Operating production systems where downtime has real consequences —
that discipline informs every engagement.