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Intelligent AI & ML Solutions
Built to Deliver Results

ADT's AI/ML team โ€” led by experts with 12+ years in Machine Learning, Deep Learning, NLP and Computer Vision โ€” delivers production-grade AI that creates measurable business impact.

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AI & Machine Learning

From Research to Production:
Real AI That Works

AnantaDrishti's AI & Machine Learning practice provides end-to-end delivery of machine learning solutions โ€” from problem framing and data engineering through model development, evaluation and production deployment. Our Managing Director brings over 12 years of hands-on expertise in ML, AI, Deep Learning, Neural Networks, NLP and Computer Vision.

We do not build demos โ€” we build AI systems that run in production, handling real data at scale. Our models are deployed on cloud infrastructure with monitoring, retraining pipelines and version control so they improve over time.

Whether you need a recommendation engine, a computer vision quality inspection system, a natural language chatbot or a predictive analytics platform, ADT has the expertise to deliver it โ€” and the experience to know when AI is the right solution and when it is not.

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Deep Learning Models
Custom neural networks for classification, detection, segmentation and generation tasks.
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Natural Language Processing
Text classification, sentiment analysis, named entity recognition, summarisation and RAG systems.
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Computer Vision
Object detection, face recognition, OCR, defect detection and video analytics pipelines.
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Predictive Analytics
Time-series forecasting, demand prediction, churn modelling and anomaly detection.
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MLOps & Deployment
Model versioning, CI/CD for ML, monitoring, drift detection and automated retraining pipelines.
Why Choose ADT

AI Built by Practitioners,
Not Just Researchers

12+ years of hands-on AI experience means we know what works in production.

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Business-Problem First

We start with your business problem, not with a model architecture. AI is a means, not the end.

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End-to-End Delivery

Data pipeline โ†’ feature engineering โ†’ model training โ†’ evaluation โ†’ deployment โ†’ monitoring. We own it all.

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State-of-the-Art Models

Access to the latest architectures โ€” transformers, diffusion models, LLMs, vision models and more.

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Cloud-Native Deployment

Models deployed on Azure ML, AWS SageMaker or GCP Vertex AI with auto-scaling and cost control.

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Explainable AI

SHAP, LIME and model cards so you understand what your AI is doing and why.

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Continuous Improvement

Automated monitoring for data drift, performance degradation and retraining triggers.

Use Cases

Real-World Applications

How businesses across India are using ADT's AI & Machine Learning services to drive growth.

Quality Control Vision

Computer vision system detecting manufacturing defects on a production line โ€” reducing QC costs by 60%.

Customer Churn Prediction

ML model predicting customer churn 30 days in advance for a telecom company, enabling proactive retention.

Document Intelligent Extraction

NLP pipeline extracting structured data from scanned invoices, contracts and government forms at 95% accuracy.

Demand Forecasting

Time-series ML model predicting product demand for a retail chain across 50+ SKUs and 20 locations.

AI Chatbot for Healthcare

NLP-powered patient query chatbot for a hospital group handling 5,000+ queries per day in Hindi and English.

Anomaly Detection in IoT

Unsupervised anomaly detection on industrial sensor streams detecting equipment failure 48 hours in advance.

Technologies

Tools & Technologies We Use

Industry-standard technologies chosen for performance, reliability and scalability.

Python PyTorch TensorFlow Keras Scikit-learn Hugging Face Transformers LangChain OpenAI API OpenCV YOLOv8 FAISS Pandas NumPy MLflow DVC FastAPI Docker Azure ML AWS SageMaker Weights & Biases
Our Process

How We Deliver It

A structured, transparent delivery process that keeps you informed at every step.

01

Problem Framing

Define the ML problem, success metrics, data requirements and business value clearly.

02

Data Assessment & Pipeline

Audit available data, design collection/labelling pipelines and build reproducible data workflows.

03

Exploratory Analysis

EDA, feature engineering, baseline models and hypothesis testing to validate the approach.

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Model Development

Train, tune and evaluate models using rigorous cross-validation and held-out test sets.

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Productionisation

Build APIs, containerise models and deploy to cloud with monitoring and logging infrastructure.

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Monitor & Retrain

Track production performance, detect drift and run automated retraining pipelines on schedule.

AI & Machine Learning at ADT
AI Projects Delivered
50+
Avg. Accuracy Improvement
35%
Model Serving Latency
<200ms
AI Experience (MD)
12+ Years
Production Models Running
30+
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Ready to Get Started?

Talk to our AI & Machine Learning team today and let's build something extraordinary.

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