AutoML & Custom Model Development
Accelerate Innovation with Tailored ML Solutions & Deployment Pipelines
At Banao Technologies, we build and deploy custom machine learning models that solve unique business challenges—fast. Our AutoML platforms automate the entire ML lifecycle, while our expert team crafts bespoke models for complex data, advanced analytics, and predictive applications. Unlock the power of AI, reduce development time, and ensure scalable deployment with our end-to-end ML services.
AutoML & Custom ML: Democratizing Data Science
AutoML platforms streamline data preprocessing, model selection, training, and validation—enabling rapid prototyping and deployment of ML solutions. For unique or complex problems, custom ML models deliver domain-specific accuracy and control. With our hybrid approach, you can leverage automation for speed and customization for precision, transforming raw data into actionable intelligence.
What We Build with AutoML & Custom ML
Our ML development services cover everything from automated workflows to bespoke algorithms—empowering you with solutions that fit your data and vision.
Let's Build Your ML Solution
AutoML Platform Setup & Integration
Deploy and configure leading AutoML platforms—automating data preprocessing, model training, and hyperparameter tuning for faster results.
Custom Model Design & Development
Develop models tailored to your business needs—classification, regression, clustering, recommendation, anomaly detection, and more.
Data Preparation & Feature Engineering
Clean, transform, and engineer features from raw data—maximizing model performance and reliability.
Model Validation & Explainability
Validate model outputs with cross-validation, bias checks, and explainable AI techniques for transparency and trust.
Deployment Pipelines & MLOps
Automate model deployment with CI/CD pipelines, monitoring, and versioning—ensuring reliable, scalable, and secure production workflows.
Model Monitoring & Retraining
Track model performance in real time, retrain on new data, and update pipelines for ongoing accuracy and improvement.
Edge Deployment & Optimization
Optimize models for deployment on mobile, IoT devices, or edge systems—enabling real-time AI at scale.
Custom API & Integration Services
Expose models via secure APIs, integrate with your business applications, and enable seamless data workflows.
Industries We Empower with AutoML & Custom ML
Retail & E-commerce
Power recommendation engines, demand forecasting, and personalized marketing with custom ML models.
EdTech & Learning
Deliver adaptive learning, student performance analytics, and intelligent content recommendations.
Healthcare & Life Sciences
Enable disease prediction, medical image analysis, and patient risk modeling with domain-specific ML.
Banking & Finance
Automate credit scoring, fraud detection, and financial forecasting with robust, explainable models.
Manufacturing & Logistics
Optimize production schedules, predictive maintenance, and supply chain planning with advanced ML.
Telecom & Utilities
Predict churn, optimize network performance, and automate service delivery with scalable ML solutions.
Recent Work
Design | Web Development | AutoML & Custom ML
Custom Churn Prediction Model
In 2024, we developed and deployed a custom churn prediction model for a telecom client—cutting attrition by 30% and boosting retention strategies using AutoML-driven rapid prototyping.
Our AutoML & Custom ML Development Process
Discovery & Problem Definition
We begin by analyzing business objectives, available datasets, and industry challenges to define high-impact ML use cases. Our team establishes measurable KPIs to ensure AI and predictive analytics initiatives align with business growth and ROI.
Data Preparation & Feature Engineering
We clean, normalize, and enrich raw data while engineering meaningful features that maximize machine learning accuracy. This ensures strong model performance, data quality, and readiness for large-scale AI training.
Model Selection, Training & Tuning
Our experts evaluate AutoML platforms and custom-built algorithms to identify the best approach. We train, fine-tune, and optimize models using regression, classification, and deep learning methods for superior predictive power.
Validation & Explainability
Each model undergoes rigorous validation with real-world test data, accuracy scoring, and fairness checks. We integrate AI explainability tools to provide transparent, bias-free predictions that build stakeholder trust.
Deployment & Integration
We deploy ML models through secure APIs, cloud services, or on-premise infrastructure. Our team integrates solutions with enterprise applications, business dashboards, and data pipelines for seamless AI adoption.
Monitoring & Continuous Improvement
Post-deployment, we provide proactive monitoring, drift detection, and automated retraining. This continuous MLOps cycle ensures long-term accuracy, resilience, and scalability of your machine learning solutions.
Client Voices: Custom ML Success Stories
Sonal Verma
Chief Data Officer, FinEdge
Oliver Chen
Lead Analyst, RetailBoost
Tailored ML, real results
Banao’s custom credit scoring model improved our risk assessment and reduced defaults. Their data science expertise is top-notch.
Where we're located
Let's Build Something Great Together. 🤝
Here is what you will get for submitting your contact details.
45 minutes of free consultation- A strict non-disclosure agreement
- Free market & competitive analysis
- Suggestions on revenue models & planning
- Detailed feature list document
- No obligation proposal
- Action plan to kick start your project
Frequently asked questions
What is AutoML and how does it differ from custom ML?
AutoML automates model selection, training, and tuning. Custom ML involves building domain-specific models tailored to complex or unique business needs.
Can you build and deploy models for my specific data?
Absolutely. We develop and deploy models tailored to your data, objectives, and industry context for maximum impact.
How do you ensure accuracy and explainability?
We validate models using robust metrics, monitor for bias, and provide explainable AI techniques for transparency.
What is the typical timeline for ML model development?
Rapid prototypes using AutoML can be ready in 2–4 weeks. Custom model development and deployment may take 1–3 months, depending on complexity.
Do you support model monitoring, retraining, and MLOps?
Yes. We deliver end-to-end MLOps, including live model monitoring, retraining pipelines, and version management for continuous improvement.