Question 1

What is a custom AI model and why do I need one?

Accepted Answer

A custom AI model is specifically trained on your business data to solve your unique challenges. Unlike generic pre-trained models, custom models understand your domain-specific terminology, patterns, and requirements, providing superior accuracy and relevance. You need a custom model when off-the-shelf solutions don't meet your specific business needs or when dealing with proprietary data and processes.

Question 2

How much data do I need to train a custom AI model?

Accepted Answer

Data requirements vary by task complexity. For simple classification, 1,000-5,000 labeled examples might suffice. Complex tasks like NLP or computer vision typically need 10,000-100,000+ examples. We can also use transfer learning and data augmentation techniques to achieve good results with smaller datasets. During consultation, we'll assess your data and recommend the best approach.

Question 3

What is the process for developing a custom AI model?

Accepted Answer

Our process includes: 1) Requirements analysis and data assessment, 2) Data collection, cleaning, and labeling, 3) Feature engineering and preprocessing, 4) Model architecture selection, 5) Training and hyperparameter tuning, 6) Validation and testing, 7) Deployment to production, 8) Monitoring and continuous improvement. Typical timeline is 2-6 months depending on complexity.

Question 4

Can you fine-tune existing models like GPT or BERT for my use case?

Accepted Answer

Yes! We specialize in fine-tuning pre-trained models (GPT-3/4, BERT, Llama, YOLO, ResNet, etc.) for domain-specific applications. This approach leverages the knowledge of large models while adapting them to your specific needs, often requiring less data and time than training from scratch. We've successfully fine-tuned models for legal, medical, financial, and industrial applications.

Question 5

How do you ensure my custom AI model remains accurate over time?

Accepted Answer

We implement continuous monitoring, automatic performance tracking, data drift detection, and regular model retraining pipelines. We set up MLOps infrastructure to monitor key metrics, alert on performance degradation, and automatically retrain models with fresh data. We also provide ongoing maintenance packages to ensure your model stays accurate as your business evolves.

Question 6

What is the cost of developing a custom AI model?

Accepted Answer

Costs range from ₹5,00,000 for simple models to ₹50,00,000+ for complex deep learning systems. Factors affecting cost include: data volume and quality, model complexity, training infrastructure requirements, deployment needs, and ongoing maintenance. We offer flexible pricing including fixed-price projects, time & material, and dedicated team models. Contact us for a detailed quote.

Custom AI Models Development

Custom AI Models We Build

Custom NLP Models

Computer Vision Models

Predictive Models

Recommendation Models

Anomaly Detection Models

Speech & Audio Models

Our Model Training Services

Data Preparation & Labeling

Model Architecture Design

Training & Fine-Tuning

Model Evaluation & Testing

Model Deployment

MLOps & Monitoring

Pre-trained Model Fine-Tuning

Language Models

Vision Models

Audio Models

Why Fine-Tune Instead of Training from Scratch?

✓ Faster Development

✓ Less Data Required

✓ Lower Costs

✓ Better Performance

Our Model Development Process

Phase 1: Discovery & Planning

Phase 2: Data Preparation

Phase 3: Model Development

Phase 4: Testing & Validation

Phase 5: Deployment

Phase 6: Monitoring & Optimization

Custom AI Model Pricing

Basic Model

Advanced Model

Enterprise Model

Frequently Asked Questions

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