From raw data to actionable intelligence—custom machine learning models that drive your business goals
Why Custom Models Make the Difference
Off-the-shelf AI tools can only take you so far. To create truly impactful solutions—whether it’s predicting customer churn, classifying documents, detecting fraud, or understanding human language—you need custom-trained machine learning models designed around your unique data and objectives.
At AK Technolabs, our Model Development service is where your AI solution takes shape. We don’t just train models—we build decision engines that serve your business in real time.
What Our Model Development Services Include
We follow a methodical, business-aligned approach to developing machine learning models that are accurate, scalable, and explainable.
- Use Case Definition
Clearly defining business objectives—forecasting, classification, anomaly detection, NLP, recommendation, or computer vision. - Model Selection & Design
Choosing the right algorithms (e.g., decision trees, neural networks, transformers) and architectures based on your data and performance requirements. - Training & Tuning
Running experiments, hyperparameter optimization, and feature engineering to boost accuracy and minimize overfitting. - Validation & Evaluation
Testing models using cross-validation, confusion matrices, ROC curves, and business-aligned metrics. - Deployment Readiness
Preparing models for integration with production systems, ensuring performance and scalability. - Ethics & Explainability
Implementing fairness checks, bias mitigation, and model interpretability techniques like SHAP or LIME.
Case Study: Predicting Delivery Delays for an E-commerce Logistics Platform
Client: A regional e-commerce logistics company operating in multiple cities
Objective: Predict late deliveries based on order metadata, weather, and driver history
Duration: 8 weeks
Tech Stack: Python, Scikit-learn, LightGBM, Jupyter Notebooks, AWS S3, SageMaker
Step-by-Step Process
- Business Understanding & Data Review
Identified KPIs including on-time delivery rate, customer satisfaction score, and logistics cost per order. - Feature Engineering
Created 60+ features including average driver delay, weather conditions, traffic zones, and historical delivery windows. - Model Selection
Evaluated logistic regression, random forest, and gradient boosting (LightGBM). Selected LightGBM due to performance and speed. - Training & Validation
Used k-fold cross-validation and early stopping. Achieved 92% accuracy and a recall of 87% on late delivery detection. - Model Deployment
Exported the model into AWS SageMaker endpoint with daily auto-refresh using updated data pipelines. - Business Integration
Enabled proactive re-routing of deliveries and preemptive customer notifications—resulting in higher satisfaction and reduced refunds.
Key Results
- Increased delivery prediction accuracy by 92%
- Reduced late deliveries by 28% in high-traffic zones
- Saved $100K in logistics penalties over 6 months
- Improved Net Promoter Score (NPS) by 16 points through proactive alerts
Build Intelligence That Works for You
Every AI product starts with a model—but not every model is built with your goals in mind. At AK Technolabs, we partner with you to design, test, and deploy custom AI models that deliver measurable business value.
Explore more of our AI App Development Services or contact us to discuss your specific machine learning needs.
