Risk reduction on AI investment — from whiteboard to production.
Francis Paul C. Flores builds LLM and automation systems that survive contact with real data, real users, and real edge cases. Fine-tuned NLP, agentic workflows, and analytical dashboards — shipped, not demoed.
Top 0.1%
of 32M+ members · Notebooks Expert
High-impact papers
The Lancet · Nature Medicine · The Lancet Public Health · JAMA Network Open
KE Excellence
Knowledge Exchange Excellence Award (2024)
95%+ Faster
Reporting turnaround reduction · 20 hrs/week reclaimed
5M+ Rows
Automated end-to-end pipelines processing government data
Production-grade AI — not demos.
Four capability areas built from real delivery history. Each maps to a specific class of business bottleneck that AI can eliminate.
Agentic Workflow Automation
Multi-agent orchestration, automated reporting pipelines, and end-to-end data workflows that reclaim hundreds of analyst-hours.
- 95%+ reporting turnaround reduction
- 20 hrs/week reclaimed
Fine-Tuned Classification Engines
Production multilingual text classifiers — XLM-RoBERTa, LoRA/QLoRA — that replace manual coding work with calibrated, auditable models matching human-level agreement in a fraction of the time.
- 80% Human Agreement
- Weeks → Hours
- EN / Traditional Chinese
Predictive & Forecasting Systems
Forecasting and risk-modeling pipelines — ARIMA, Prophet, LSTM, mixed-effects panel models — that convert historical and longitudinal data into forward-looking, decision-ready projections, validated to the same rigor as peer-reviewed research.
- 5M+ Rows Modeled
- Peer-Reviewed (Lancet · JAMA)
- ARIMA · Prophet · LSTM
Analytics & Decision-Automation Dashboards
Python/Plotly/Shiny reporting suites that turn raw data into executive-ready visualizations with zero manual overhead.
- Real-time pipeline monitoring
- Automated distribution
How I Work
A repeatable three-phase approach that de-risks every engagement — from discovery through production deployment.
Bottleneck Assessment
We start with a structured discovery session to map your current workflow, identify bottlenecks, and quantify the opportunity. You get a clear ROI projection before any engineering begins — no blind commitments.
- Current-state workflow audit
- Data source & quality assessment
- ROI projection with conservative assumptions
Proof of Value
I build a rapid prototype against your real data — not a toy demo. You see whether the approach works on your actual edge cases before we commit to a full build.
- Rapid prototype on real data
- Edge-case validation
- Architecture & cost estimate for production scale
Production Delivery
The prototype is hardened into a production system: automated pipelines, monitoring, documentation, and handover. You own the code and the system from day one.
- Deployment & pipeline automation
- Monitoring & alerting
- Documentation & knowledge transfer