Custom AI Models
AI built for your business, not off-the-shelf.
We develop custom machine learning models that solve your specific problems. Recommendation engines, fraud detection, demand forecasting—trained on your data, optimized for your goals.
- Recommendation engines that increase engagement and revenue
- Anomaly detection for fraud, quality, and security
- Custom classifiers and scoring models
- Models trained on your proprietary data
- Explainable AI for stakeholder buy-in
- Production deployment with monitoring
AI built for your business, not off-the-shelf.
AI & Machine Learning
Technologies We Use
Enterprise-grade ML tools and frameworks
What we deliver
Production-ready AI models with the infrastructure to operate them.
Custom trained models
Models optimized for your specific use case and data.
Inference APIs
RESTful APIs for real-time predictions with batch support.
ML pipeline
Automated training, validation, and deployment infrastructure.
Model documentation
Feature importance, performance metrics, and operational guides.
How We Work
A proven methodology for building AI that works in production.
Problem Framing
Define the business problem, success metrics, and data requirements.
Data Preparation
Clean, transform, and engineer features from your data.
Model Development
Train, validate, and optimize multiple model architectures.
Production Deployment
Deploy with APIs, monitoring, and automated retraining pipelines.
Engagement models
Structured options from proof-of-concept to AI platform builds.
AI POC
Validate feasibility with sample data and baseline model.
$15,000 - $25,000
Production model
Full model development with APIs, monitoring, and training.
$40,000 - $70,000
AI retainer
Ongoing model optimization and new model development.
$10,000 - $20,000/mo
Certifications & Partners
What clients are saying
Results from custom AI implementations we've built.
"The recommendation engine increased average order value by 23%. Best AI investment we've made."
"Fraud detection catches patterns our rules missed. False positives dropped 60%."
"The scoring model prioritizes leads that actually convert. Sales efficiency up 35%."
Frequently asked questions
How much data do I need?
It depends on the problem. Classification may need 1,000+ labeled examples; recommendations work with user behavior data. We assess during discovery.
How long does it take to build a custom model?
POCs take 4-6 weeks. Full production models typically take 8-14 weeks depending on complexity and data readiness.
Can you explain how the model makes decisions?
Yes. We use explainability techniques (SHAP, LIME) to show feature importance and decision factors. Critical for stakeholder trust.
What if the model doesn't perform well?
We establish benchmarks early. If a model can't beat baselines, we're transparent about limitations and pivot to alternative approaches.
Ready to build AI for your business?
Share your problem and data. We'll assess AI feasibility and potential impact in a 30-minute call.
Subscribe and start making the most of every engagement.
