14+ years across operations, technology, and client delivery
Customer service, risk, project management, marketing, and technical operations roles across agencies, startups, and her own companies — before any of it involved AI.
Founder · AI Systems Consultant
Fourteen-plus years across customer operations, risk, project management, and staffing — a career that runs from managing frontline service teams to founding and exiting a 100-plus-client outsourcing company, to designing AI systems for other businesses today. Every stop added a different kind of operational judgment; AI is the newest tool applied to the same instincts.
Nyrriel's first decade was spent earning operational judgment the hard way — running a customer service team, then moving into risk and compliance review, then project management, then a marketing leadership seat. By 2018 she had enough of a pattern-read on how service businesses actually break to found her own: an outsourcing and staffing company that grew to serve 100-plus international clients before she exited it in 2026. In parallel, she took on senior operating roles — managing AI-facing data quality for an analytics team, running day-to-day operations for a remote technology company, and serving as Chief of Staff across a multi-business portfolio — before founding Workroom Asia™ in 2024 and moving into independent AI automation consulting. The throughline across all of it: she has sat on both sides of "does this actually work" — as the operator responsible for the outcome, and now as the person designing the system.
Customer service, risk, project management, marketing, and technical operations roles across agencies, startups, and her own companies — before any of it involved AI.
Automation gets designed with a real checkpoint where someone verifies the work, not just a pipeline that runs and hopes — a habit formed managing AI-facing data quality long before it became a design principle.
Comfortable in the same room as founders, developers, analysts, designers, and operations teams — and able to translate between them, a skill built from sitting in nearly every one of those seats herself.
Two founder ventures of her own — one scaled to 100-plus clients and exited, one still running — mean the advice comes from having actually run the business, not just advised on one.
Years spent reviewing risk and compliance cases that needed real judgment, not a checklist — the same instinct that shows up today as guardrails and escalation rules in every AI system she designs.
A career built almost entirely remote and offshore — managing teams and clients across the US and the Philippines without a shared office, long before that was the industry norm.
Claude, Claude Code, ChatGPT, n8n
Notion, Airtable, Google Workspace
FastAPI, SQLite, Git/GitHub, Vercel
Requirements docs, QA gates, human-review checkpoints, staffing & onboarding SOPs
Employer names are withheld under prior confidentiality agreements — roles, scope, and impact are described in full below.
Built without a clean API to work against — a reconciliation loop that's still learning under supervision, and a strict no-guessing rule anywhere money is involved. Read the case study →
About 80% of the workflow runs on its own, from content ideation down to sourcing the right VA — the venture she founded and still runs. Read the case study →
A persistent operating dashboard she built for her own daily prioritization, kanban, and weekly review. Read the case study →
Tell us what's manual today, and we'll map what a practical AI implementation could look like.