Business information systems
Bridging operator needs, data structures, and technology constraints without losing the business context.
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Founder profile
Chuk Uyammadu
Chukwuemelie "Chuk" Uyammadu — Information Systems Management background, IT support and data analysis experience, backend and AI systems builder, Linux homelab operator, and small-business technology practitioner.
Engineering identity
Building practical technology systems for real-world operations
I build technology systems at the intersection of software development, data analytics, infrastructure engineering, and business operations. The strongest work starts with operational problems: a business needs clearer reporting, a workflow needs automation, a local system needs reliable uptime, or a prototype needs enough structure that technical reviewers can trust it. Every project is scoped in writing, built on maintainable patterns, and documented for handoff.
Education signal
Information Systems Management
Business systems, process thinking, data workflows, and technology management.
Experience signal
IT support + data analysis
Troubleshooting, reporting, operational visibility, and owner-friendly handoff.
Build signal
Python, backend, AI systems
FastAPI-style services, structured data contracts, agent prototypes, and eval checks.
Operator signal
Linux homelab + small business
Raspberry Pi systems, local infrastructure, restaurants, cameras, networks, and daily operations.
Operator stack
Tools used to build, run, and review the work
Compact, owner-controlled stack across local infrastructure, backend services, data storage, and AI-assisted development.
Local infrastructure
Raspberry PiLinuxDockersystemdCloudflare TunnelTailscale
Backend + data
PythonRustFastAPIAxumSupabaseSQLite/Postgres
AI-assisted tooling
CodexHermesClaudeIBM Bob
Capability scan
Where the work clusters
The portfolio is intentionally practical: systems that read local data, automate narrow workflows, support business decisions, and remain explainable.
Backend and AI prototypes
Python services, API surfaces, typed responses, guardrail patterns, and reviewer-visible execution trails.
Data analyst instincts
Turning CSV exports, POS reports, and operational data into summaries people can act on.
Hands-on infrastructure
Raspberry Pi, Linux, networking, cameras, local services, and the documentation needed to hand systems off.
Representative projects
- Orion: safe AI business intelligence prototype with fictional local data, read-only connectors, and reviewer-visible decision trails.
- Raspberry Pi infrastructure pattern: small-business local services and owner-controlled systems.
- Camera systems practice: privacy-first camera/NVR planning, remote access, and handoff documentation.
Working style
- Scope the business problem before picking a tool.
- Prefer read-only, inspectable, and reversible workflows where risk matters.
- Write handoff notes so the owner or reviewer understands what changed.
- Keep public claims bounded to what is actually built or demonstrable.
Review the work, then start with the case studies.
Orion is the clearest backend/AI example; the camera and infrastructure work shows the operator side.