AI That Works
For Business.
We design, train, and deploy custom machine learning models that solve real problems — from demand forecasting to LLM assistants and edge AI.
ML That Doesn't
Stay in the Notebook.
85% of ML models never make it to production. We build full MLOps pipelines to ensure your models are trained, versioned, deployed to scalable endpoints, and monitored for data drift in real time.
- Automated model retraining pipelines (CI/CD for ML)
- Containerized inference endpoints using FastAPI & Docker
- Hardware acceleration (TensorRT, ONNX) for sub-ms latency
- Continuous data drift and model performance monitoring
Every ML Capability.
Production-Ready.
Custom ML Model Development
We build, train, and deploy bespoke machine learning models on your proprietary data using PyTorch, TensorFlow, and Scikit-learn. Whether it's forecasting, classification, anomaly detection, or NLP, every model is tailored.
Edge AI & On-Device Inference
Deploy optimised ML models directly to edge hardware — IoT devices, NVIDIA Jetson boards, mobile, and embedded systems. Our quantisation shrinks model size by up to 80% enabling real-time AI without cloud dependency.
Predictive Analytics
Turn your historical data into forward-looking intelligence. We design time-series forecasting models, demand planning engines, and churn predictors — all delivered with explainable dashboards.
LLM Fine-Tuning & Integration
Fine-tune and deploy OpenAI GPT, Anthropic Claude, or Google Gemini models on your domain-specific data. We handle prompt engineering, retrieval augmentation (RAG), and production-grade API delivery.
MLOps & Production Engineering
Machine learning doesn't end at the notebook. We productionise your models with FastAPI endpoints, Docker deployments, CI/CD pipelines, and real-time monitoring with data drift detection.
Responsible & Explainable AI
We build fairness audits, SHAP/LIME explainability layers, and bias detection into every model we ship. Regulatory compliance (GDPR, EU AI Act) and stakeholder trust are engineered from day one.
Applied Across
Every Vertical.
- Computer vision defect detection
- Predictive maintenance on factory floors
- Supply chain demand forecasting
- Personalised product recommendations
- Dynamic pricing elasticity models
- Inventory stockout prevention
- Medical imaging classification
- Patient readmission risk scoring
- LLM-powered clinical documentation
- Real-time fraud detection
- Algorithmic trading signals
- Credit risk and default prediction
The ML Economy
Is Reshaping Everything.
Annual value that generative AI and advanced ML could add to the global economy — with the largest gains in marketing, software engineering, and operations.
Of AI projects fail to deliver business value without proper ML engineering and MLOps infrastructure — making production-grade deployment the critical differentiator.
Knowledge workers using AI-augmented workflows complete tasks 37% faster with 40% higher quality scores compared to non-AI workflows.
Global enterprise AI and ML spend projected for 2028, driven by custom model development, MLOps tooling, and edge inference infrastructure.
Technology Stack
Industry-leading ML tools. Production-grade delivery.
Ready to Productionise
Your ML Strategy?
From data audit to live model in 4–8 weeks. We handle the science, the engineering, and the deployment so your team can focus on outcomes.
© 2026 AI Geek Advisor Pvt. Ltd. · New Delhi, India
We value your privacy
We use cookies to enhance your browsing experience, serve personalized ads, and analyze our traffic. By clicking "Accept All", you consent to our use of cookies. For more details, see our Privacy Policy.