AI That Delivers Measurable Business Outcomes
We build AI and machine learning systems that solve specific, high-value business problems. Not AI for the sake of AI — but predictive models, intelligent agents, and computer vision systems that reduce cost, increase throughput, or unlock capabilities your team doesn't have today.
Our AI work is production-proven. We have live systems handling automated interview scheduling, real-time lead qualification, tire safety classification, and 24/7 university student support. These aren't demos — they're running in production and delivering results.
Based in Baguio City, Philippines, we work with local businesses and international clients who want AI built by engineers who understand both the technology and the business context it needs to serve.
Your data is already generating competitive advantage — for someone else
Most businesses accumulate years of customer data, transaction records, operational logs, and documents — and use almost none of it for decision-making. The data exists; the infrastructure to extract value from it doesn't.
Meanwhile, competitors who've invested in predictive models know which customers are about to churn before the customer does. Competitors with computer vision systems catch quality defects in seconds that manual inspection misses for hours. Competitors with AI agents are qualifying ten times as many leads with the same headcount.
The entry point to applied AI has dropped dramatically. You don't need a team of researchers or a massive data infrastructure. You need the right problem, the right data, and engineers who know how to build production ML systems — not just run notebooks.
What we've shipped in production
AI SMS Scheduler
Automated interview scheduling and reminders via intelligent SMS agents
n8n · DeepSeek · Twilio
Leads Data AI Enrichment
Real-time outbound calling agents with data enrichment for lead qualification
Vapi · OpenAI · Apollo
Tire Thread Classifier
Computer vision model for automated tire wear analysis and safety classification
YOLOv8 · Roboflow · FastAPI
University AI Chatbot
Intelligent student support assistant providing 24/7 answers to academic queries
Rasa · Ollama · Vector DB
What we build
Four AI capability areas where we have production experience and proven results.
Predictive Analytics
Turn your historical business data into forward-looking signals. We build models that predict customer churn, demand forecasting, maintenance windows, and sales performance — giving your team the information to act before problems occur, not after.
NLP & Conversational AI
Chatbots and voice agents that handle real queries — not the scripted, dead-end flows users hate. We build on large language models (OpenAI, local Ollama deployments) and retrieval-augmented generation to create assistants that give accurate, contextual answers from your own data.
Live example: University AI Chatbot — 24/7 student support assistant built on Rasa + Ollama
Computer Vision
Automated visual inspection, object detection, and image classification systems. We've deployed models for quality control, safety compliance, and inventory counting using YOLOv8 and custom-trained convolutional networks. These replace manual inspection workflows that are expensive, slow, and inconsistent.
Live example: Tire Thread Classifier — automated safety classification model, live in production
Intelligent Process Automation
AI agents that handle multi-step workflows autonomously — scheduling, lead qualification, data enrichment, document processing, and more. Not simple rule-based bots, but agent systems that handle exceptions, make decisions, and escalate to humans when needed.
Live example: AI SMS Scheduler — automated interview scheduling via intelligent SMS agents, live in production
How we approach AI projects
We start every AI engagement with a scoping session to establish two things: what data you actually have, and what business decision the AI needs to support. These two constraints determine everything — which approach to use, how long it will take, and what result is realistic.
We don't oversell AI capabilities. If your problem is better solved by a well-designed rules engine or a standard analytics dashboard, we'll tell you. When machine learning is the right tool, we'll show you why and build it correctly — with proper training/evaluation splits, monitoring in production, and a retraining plan for when the model drifts.
All our AI systems come with an API layer (FastAPI or Node.js) so they integrate cleanly into your existing applications. AI that lives only in a Jupyter notebook is a prototype. AI that's behind an API and deployed in production is a product.
Our AI/ML stack
From problem to production
Problem Scoping
Define the business decision being made, the data available, and what a good outcome looks like. Sets realistic expectations before any code is written.
Data Assessment
Review your data quality, volume, and structure. Identify gaps and preprocessing requirements. This step determines what's actually buildable.
Model Development
Iterative model development with clear evaluation metrics. We show results against benchmarks, not just accuracy scores that look good on paper.
Production Deployment
API-wrapped deployment with monitoring, alerting, and a retraining schedule. The model doesn't end at handoff — it runs and improves over time.
Have a problem AI could solve?
Tell us what you're trying to automate, predict, or classify. We'll give you an honest assessment of what's possible with your data.
Get in Touch