IT Systems · Data Integrity · Automation · Governance

Building systems that can be verified, audited, and improved.

I work across IT operations, automation, data workflows, web systems, QA, and engineering governance. My approach is evidence-first: understand the dependency, validate the data, identify the failure mode, and build a system that makes the result traceable.

About Jan Michael Acibron

The person behind RankFixer and the systems, automation, and research work that support it.

Founder · Builder · Systems Thinker

I build systems around evidence, not assumptions.

I'm Jan Michael Acibron, an IT and digital systems professional with 16+ years of experience across technical support, QA, web operations, automation, data workflows, eCommerce, and remote business operations.

My work increasingly focuses on building systems that can collect information, validate it, trace where it came from, identify failure conditions, and turn the result into something useful for a real decision.

RankFixer is one expression of that approach: a system for understanding website and AI visibility through structured evidence rather than unsupported claims.

Engineering Principle

Verification is the foundation. A system should be able to explain what happened, preserve the relevant evidence, and expose uncertainty instead of hiding it.

Evidence First Traceability Data Integrity Auditability No Silent Failure

Truth Before Persuasion

I separate verified facts from hypotheses and avoid presenting confidence as evidence. If evidence is insufficient, the correct engineering decision is to say so.

Systems Over Symptoms

When something breaks, I look beyond the visible error and trace dependencies across data, workflows, APIs, applications, and operational processes.

Automation With Controls

Automation should not simply make a process faster. It should make the process more consistent, observable, recoverable, and easier to audit.

Why RankFixer

Turning complex signals into governed decisions.

RankFixer brings together website analysis, AI visibility research, data collection, structured extraction, and automation. The goal is not to produce another black-box score. The goal is to create a traceable path from source data to evidence, from evidence to analysis, and from analysis to an actionable decision.

PMOS — Governed Execution

A provenance-managed, fail-closed governance layer controlling how work becomes authorized, released, and deployed.

No evidence → no authority. No authority → no execution.

PMOS (Provenance-Managed Operating System) sits around the execution system and governs the full path from objective through execution, evidence, validation, decision, and authorization, to release and deployment. Execution results do not automatically become governance decisions: evidence must pass explicit gates before authority is granted.

It is deliberately fail-closed. Missing or corrupt governance state stops execution rather than silently recovering into an unsafe state. It refuses to invent evidence, promote incomplete evidence, bypass authority, overwrite decisions, or treat an external result as a governed decision without an explicit governance act. Governance decisions are records, not mutable configuration.

CosmosOS is the dashboard component of this project — the surface where verification, system health, and governance events become observable. The governing rule is the same one RankFixer follows: truth before persuasion. If evidence does not establish that something is safe, authorized, or verified, the system stops rather than filling the gap with assumptions.

Systems & Applications

Systems and tools I build and use across research, automation, and operations.

SYSTEM 01

RankFixer

AI visibility tools, free scanning, diagnosis, structured website analysis, and report generation.

AISEOPythonScrapingAPIs
SYSTEM 02

Competitive System

Finds competitors, scores threats, analyzes competitive conditions, and supports content strategy.

ResearchScoringAutomation
SYSTEM 03

Job Alert System

Automated job discovery, scoring, alert processing, and application-generation workflows.

Data PipelineAlertsAutomation
SYSTEM 04

Client Onboarding

Seven-phase onboarding workflow with verified milestones and structured process progression.

WorkflowVerificationProcess Design
SYSTEM 05

LLM Bridge

Structured AI extraction across multiple domains, designed to turn unstructured information into validated data.

LLMExtractionJSONValidation

Technical Stack

Tools and technologies used across systems, automation, data, web development, and operations.

PythonJavaScriptHTMLCSS Next.jsTailwind CSSFastAPIReact/Vite SupabaseGoogle Apps ScriptREST APIsJSON n8nBeautifulSoupSeleniumWordPress Google WorkspaceMicrosoft OfficeAsanaSlack TrelloNotionMondayHubSpot Google AnalyticsLLMsRAGPrompt Engineering
Contact

Interested in systems, automation, data integrity, or technical operations?

I am available for IT systems, automation, data operations, technical support, QA, web technology, and engineering-oriented roles where reliable systems and evidence-based problem solving matter.